Добірка наукової літератури з теми "Policy scenario"

Land use/Land cover (LULC) changes as a result of policy planning influence ecosystem structures, processes, and functions, which are the basis for providing a wide range of ecosystem services (ES). There is an increasing consensus about the importance of integrating ES into ecological policy but quantifying the potential impacts of different policy on ES has proven difficult. We designed a remote sensing, geographic information system and scenario analysis-based approach to estimate and analyze the relationship between ES (soil conservation and carbon sequestration) and ecological policy designed to improve human welfare in the Chongqing municipality in the upper reaches of the Three Gorges Reservoir Area, China; a densely populated, highly modified watershed with serious soil erosion and flood hazard. Three alternative scenarios in 2050 were modeled for the Three Gorges Reservoir Area watershed. The model GEOMOD was used to predict future LULC changes due to policy planning. The ES models (Universal Soil Loss Equation model and Carnegie-Ames-Stanford Approach model) were designed to inform decisions, with an aim to align economic forces with conservation. We examine policy effectiveness by comparing scenarios for 2050 (Scenario1: Maintain current policy with no considerations of ES; Scenario2: Integrate ES into policy planning; Scenario3: Integrate ES into policy planning in view of the need of local people). Scenario-based LULC change analysis revealed that if the current afforestation policy continues (scenario 1), total ES would be further increased in 2050 due to expansion of forest cover. However, by targeting policy to improve ES provision (scenarios 2 and 3), ecological risks of soil loss can be significantly reduced and carbon sequestration enhanced. Scenario 3, thus, provided the best future environmental development scenario considering the need of local people in each region for ES. This scenario will theoretically help the Three Gorges Dam to harvest more ecological benefits through improvements in soil conservation and carbon sequestration. This study highlights the observation that including ES in policy planning and has a great potential to generate opportunities to maximize ES. This study highlights that including ES in policy planning has a great potential to generate opportunities to maximize ES. Hence, there is a need to encourage proper implementation of ecological policy to maintain and improve ES.

Due to global climate change, various countries have agreed upon the use of conventions. In this study, the eco-friendly vehicular policy on carbon neutrality implemented in Seoul, Korea, was examined. To this end, various policy-based scenarios were set, and the changes in automotive exhaust gas emissions were evaluated and compared. The evaluation method combined macroscopic and microscopic emission models as its analysis framework. Micro-traffic data available in Korea were used for analyses, and the results for all autonomous districts were derived to cover the entire area of Seoul. The findings confirmed that the most effective measure is the initial replacement of old, mid-size, or large diesel passenger cars with eco-friendly vehicles (Middle-sized: Scenario 2-1 5.52%, Scenario 2-2 6.86%, Scenario 3-1 80.93%, and Scenario 3-2 83.98%). The replacement of old vehicles exhibited the highest effect in all tested scenarios, while the initial replacement of diesel vehicles was more effective than the replacement of gasoline and liquified petroleum gas vehicles (Diesel: Scenario2-1 6.64%, Scenario 2-2 8.21%, Scenario3-1 86.23%, and Scenario 3-2 90.51%). Among the autonomous districts of Seoul, the Gangnam-gu area exhibited the largest emission-reduced effect among all the tested scenarios (Gangnam-gu: Scenario 2-1 5.80%, Scenario 2-2 6.74%, Scenario 3-1 80.44%, and Scenario 3-2 82.62%). Overall, it was demonstrated that the findings of this study may have significant policy implications in terms of urban emission changes pertaining to transportation.

The main objective of this paper is to create scenarios of possible development of social policy in the Czech Republic and evaluate the probability of each scenario. Based on the literature review and scenario method, three scenarios are created (scenario of a positive development, scenario of a negative development, and explorative scenario), which are compared with the current state of Czech social policy and which evaluate the possible development of Czech social policy in the period up to 2050. For the implementation of scenarios, basic factors that influence the development of Czech social policy are identified. The complementary research methods are creative methods brainstorming and mind mapping, modelling, an intuitive method of estimating trends and decision-making method of scoring. The research shows that the Czech social policy system is threatened without accepting the strategic and conceptual social policy solutions. The probability of the scenario of negative development (critical scenario) of Czech social policy is more than ninety percent. This scenario is based on a deep economic crisis, the collapse of the entire system of social policy and great social unrest. The created scenarios are useful for actors of social policy which can reverse the negative development of Czech social policy.

Abstract. The effectiveness of population policy scenarios in reducing the combined impacts of population change and climate change on water resources is explored. One no-policy scenario and two scenarios with population policy assumptions are employed in combination with water availability under the SRES scenarios A1b, B1 and A2 for the impact analysis. The population data used are from the World Bank. The river discharges per grid of horizontal resolution 0.5° are obtained from the Total Runoff Integrating Pathways (TRIP) of the University of Tokyo, Japan. Unlike the population scenarios utilized in the SRES emission scenarios and the newest Representative Concentration Pathways, the scenarios employed in this research are based, even after 2050, on country-level rather than regional growth assumptions. Our analysis implies that in combination with a more heterogeneous pattern of population changes across the world, a more convergent, environmentally friendly emissions scenario, such as B1, can result in a high-impact climate scenario, similar to A2, for the already water-stressed low latitudes. However, the effect of population change supersedes the changes in the climate scenarios. In 2100, Africa, Middle-East and parts of Asia are in extreme water-stress under all scenarios. For countries with high population momentum, the population policy scenario with fertility-reduction assumptions gained a maximum of 6.1 times the water availability in Niger and 5.3 times that in Uganda compared with the no-policy scenario. Most of these countries are in Sub-Saharan Africa. These countries represent 24.5% of the global population in the no-policy scenario and the scenario with fertility- reduction assumptions reduces it to 8.7% by 2100. This scenario is also effective at reducing the area under extreme water stress in these countries. However, the policy scenario with assumptions of population stabilization at the replacement fertility rate increases the water stress in high-latitude countries. Nevertheless, the impact is low due to the high per capita water availability in the region. This research is expected to widen the understanding of the combined impacts of climate change in the future and of the strategies needed to enhance the space for adaptation.

This study proposes a two-tier scenario planning model, consisting of scenario development and policy portfolio planning, to demonstrate the environmental sustainability policy planning process. Scenario development embodies future scenarios that incorporate the uncertainties regarding the decision values and technological alternatives. Policy portfolio planning is used to assess the selected policy alternatives under each scenario and to develop a robust and responsive plan. We organized first- and second-tier committees of 10–12 experts from diverse professional fields to undertake environmental sustainability policy planning in Taiwan. The first-tier committee generated three scenarios: “live at the mercy of the elements”, “industry convergence”, and “technology pilot”. The second-tier committee ensured that, from cradle-to-cradle (C2C), green supply chain management (GSCM), and industry symbiosis (IS), life-cycle type policies enhance green willingness and capabilities in the businesses. This is the first study to consider the first-tier process with scenario development and the second-tier process with policy portfolio planning for environmental sustainability, and contributes by considering intuitive logics approach-based scenarios and robust policies for extant portfolio plans, providing life-cycle- type policy profiles in environmental sustainability.

This paper analyses the impact of the Common Agricultural Policy (CAP) and macroeconomy on land use changes in the EU. Three scenarios are simulated up to 2030: baseline, macro scenario and policy scenario. Simulation results indicate that GDP leads to a stronger effect on land use changes than the CAP. Stronger changes in land use are observed at the crop disaggregated level than at the aggregated level for the total agricultural area, arable land, grassland and permanent crops.

This study discusses scenarios and analyzes the causal relationship of energy consumption and CO2 emissions to economic growth in Indonesia period 2010-2025. The modeling scenario is divided into 6 sections, namely BAU scenario, High scenario, Low scenario, High-Low scenario, Low-High scenario and Policy scenario. The result of scenario data is processed by performing statistical data modeling and econometric period 2010-2025. The research method used interpolation method and causality testing method. The tools are used in this research is LEAP and EViews. LEAP is used for energy modeling as well as CO2 emissions and EViews is used to manage data, analyze econometrics and statistics. The results of this study show that economic growth, energy consumption and CO2 emissions at 6 scenario indicate fluctuated competitive growth. This study proves that only 1 scenario has direct causality relationship that is only energy consumption which statistically significant influence economic growth in Policy scenario. For economic growth and CO2 emissions there are 4 scenarios that have direct causality (BAU, High, High -Low, Low-High scenario), 1 scenario has no causality relationship (Low scenario) and 1 scenario has two -way causality relationship (Policy scenario).

Active shooting violence at confined settings, such as educational institutions, poses serious security concerns to public safety. In studying the effects of active shooter scenarios, the common denominator associated with all events, regardless of reason/intent for shooter motives, or type of weapons used, was the location chosen and time expended between the beginning of the event and its culmination. This in turn directly correlates to number of casualties incurred in any given event. The longer the event protracts, the more casualties are incurred until law enforcement or another barrier can react and culminate the situation.Objective: Using AnyLogic technology, devise modeling scenarios to test multiple hypotheses against free-agent modeling simulation to determine the best method to reduce casualties associated with active shooter scenarios.Design, setting, subjects: Test four possible scenarios of responding to active shooter in a public school setting using agent-based computer modeling techniques—scenario 1: basic scenario where no access control or any type of security is used within the school; scenario 2, scenario assumes that concealed carry individual(s) (5-10 percent of the work force) are present in the school; scenario 3, scenario assumes that the school has assigned resource officer; scenario 4, scenario assumes that the school has assigned resource officer and concealed carry individual(s) (5-10 percent) present in the school.Main outcomes measured: Statistical data from modeling scenarios indicating which tested hypothesis resulted in fewer casualties and quicker culmination of event.Results: The use of AnyLogic proved the initial hypothesis that a decrease on response time to an active shooter scenario directly reduced victim casualties.Conclusions: Modeling tests show statistically significant fewer casualties in scenarios where on-scene armed responders such as resource officers and concealed carry personnel were present.

In this thesis we present a way of combining previously learned robot be- havior policies of different users. The main idea is to combine a set of policies, in tabular representation, into a final sub-optimal solution for the problem all users have contributed to. We assume that the features/differences of users are unknown and need to be extracted from the different policies generated from same user. This information is used to weight the importance of a set of actions to sum up two policies. The proposed approach has been tested on a virtual environment finding out that the combined policy works as a general policy suitable for all users, as it always selects actions that are satisfying the users at the border of the defined sensorial possibilities. All the assumptions has been finally verified on a real environment finding out all the limitations of the proposed model.

In a crisis situation in Ukraine's economy is worsening many problems in society, including a major problem is the relationship between economic and environmental component. Question detection interdependent impact of economic and ecological processes was the subject of extensive discussion and detailed analysis. This requires solving the problem analysis of ecological and economic efficiency regional policy in Ukraine. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/31702

Thesis (M.S. in Computer Science) Naval Postgraduate School, Sept. 2001.
Thesis advisor(s): Michael, James Bret; Riehle, Richard. "September 2001." Includes bibliographical references (p.135-138). Also available in print.

This thesis presents a novel policy assessment tool that serves as a decision support framework for analysis of energy policy problems involving multilevel, multidimensional and multi-stakeholder complexity. This new approach, The Energy Policy Assessment Technique (E-PAT), integrates System Dynamics Simulation and Multi-Criteria Evaluation models into a unified assessment framework. The E-PAT doubles as a systems-thinking model and a multi-criteria evaluation archetype. The E-PAT is designed for assessing policy issues, particularly those relating to energy planning in a national context. It is a suitable tool for evaluation and selection of optimal policies from competing and conflicting alternatives. To test its robustness and practical application, a case study on energy policy evaluation in Nigeria is carried out with this tool. A model of the Nigerian energy economy was constructed, and three proposed government policies for Sustainable Energy Development were evaluated relative to a Business-As-Usual case. The evaluation process identified ‘best’ policy options according to stakeholder viewpoints. The original contribution of this research is the creation of an integrated, transparent and comprehensive assessment tool, and the development of measurable Energy Sustainability Indicators (ESI), to aid policymakers in diverse policy analysis. The new tool is intended to support assessment of energy policies in relation to impacts on the economy, society and environment.

National access to modern energy is deemed by Malawi government as the driving force to attain social-economic development. To achieve this, optimal decisions in energy planning and investment are considered important. This study evaluates potential pathways that will inform better policy design and investment option in energy sector. The Integrated Assessment Modelling method has been used to integrate social, economic and environmental variables that affect energy systems, and further analyses potential energy pathways in relation to these earth systems. The Long-range Alternatives Energy Planning system (LEAP) has been used to run a continuous time series from 2008 to 2063 of the three energy policy pathways (scenarios) using: (1) the current Malawi National Policy and Strategies on Energy (MwNEP) (2) the United Nation’s Sustainable Energy for All strategy (SE4ALL) and (3) Business as Usual (REF) scenario. The analysis indicates an exponential growth in energy demand for both MwNEP and SE4ALL scenario with a slight higher demand in SEAll over MwNEP Scenario. In both cases Biomass remains an important energy source beyond the 2030. Thus, the SDG 7 will not be achieved by 2030. Similarly, energy demand trends in MwNEP and SE4ALL scenarios continue to grow beyond available energy stocks and generation capacity which will lead to a shortfall in energy supply. Environmentally, the GHGs emissions in MwNEP are higher than the SE4ALL scenario. This is reflected in the pro-environment policy objective pursued by SE4ALL scenario. In the medium-term LEAP analysis favours advancement of alternative renewable energies at household level like solar photovoltaic (PV) for lighting and sustainable biomass energy for cooking. In the long-run, scaling up the adoption of renewable energy in form of solar, wind and hydro-electricity to meet the energy gap. At the same time, designing and adhering to implementation of sustainable energy plans that cuts energy sources from fossil fuels and allow easy accesses to affordable renewable energies will result in a success of Malawi’s energy system.

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2003.
Includes bibliographical references (leaves 109-112).
The commercial and informal sectors contribute with significant amounts of emissions to the atmospheric pollution problem of the Mexico City Metropolitan Area (MCMA). It is more the case for some pollutants than for others, but, in any case, policies tackling the emissions of these sectors have been very few, and of very limited effect. Even the measurement of the emissions is believed to be underestimated, especially for the informal sector, which is mostly unaccounted for in the recent emissions inventories developed in the MCMA. This thesis intends to improve the estimation of commercial and informal emissions in MCMA, through a qualitative assessment of the range of emission sources in these sectors, and an emissions model based on the integrated scenario analysis methodology implemented in the Mexico City Program at MIT. The ultimate goal of this research is to propose and evaluate new policies to reduce commercial emissions, both formal and informal, in MCMA.
by Andres Flores Montalvo.
S.M.

Information Communication Technology (ICT) has become an integral part of conducting business within enterprises including the local government. Local government relies on the use of ICT to ensure that its objectives and goals are accomplished. The effective use of ICT within the context of local government is fundamental for the support, sustainability and growth of municipalities. Benefits associated with the effective use of ICT in local government include but are not limited to accelerated service delivery, efficiency and accountability. While these benefits cannot be disputed, it is important to realise that the use of ICT presents potential risks. Thus, good governance of ICT should be addressed in local government. However, in recent years, the Auditor-General of South Africa (AG) has identified lack of good governance of ICT in local government. Various issues have been identified as emanating from the lack of good governance of ICT and lack of adequate ICT risk assessment is a case in point. In an attempt to address the good governance of ICT local government, various documents have been formulated. However, none of these address how effective management of ICT risks can be achieved. As such, local government lacks the means to effectively address the management of ICT risk which is core to the good governance of ICT. Local government still requires urgent intervention with regard to addressing the activities of managing ICT risks, particularly ICT risk assessment. Moreover, it was revealed that the lack of adequate ICT skills and financial resources in local government elevates this problem. The above-mentioned problem is what has motivated this research study. This dissertation aims to produce an artefact in the form of an approach for ICT risk assessment in local government. It is believed that a customised approach to ICT risk assessment in local government will contribute towards solving the identified problem.

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
Objectives: This work assesses the extent and evolution of catastrophic health care expenditures (CHE) in Portugal in the years of 2000, 2005 and 2010, to reveal household factors predicting this outcome, and simulates changes in 2010 CHE levels’ following recent reforms in user charges and prices of pharmaceutical products. Methods: The main contribution of this paper is the calculus and analysis of statistical measures to capture CHE incidence, intensity, income distribution and impoverishment effects on households using INE Household Budget Surveys. A logistic model to determine statistical significance and economic effects of 38 variables on the incidence of CHE is also estimated. Finally, a scenario analysis is presented to analyse reforms concerning user charges and prices of pharmaceuticals. Results: Incidence and intensity of CHE decreased between 2000 and 2010, from 5,005% to 2,439% and 4,693% to 0,334%, respectively. During the period, CHE were concentrated amongst the poorer income quintiles. Statistical significance in CHE prediction for all analysed years was observed for households’ income, smoking and drinking habits, area of the house and secondary education of the household head. Scenario analysis shows that the new levels of user charges in 2012, even if mitigated by the new and enlarged economic exemptions, would increase CHE incidence of 2010 to 3,529%. On the other hand, the reduction in the price of ambulatory pharmaceuticals in 2011 and 2012 is effective in reducing CHE incidence, for price demand elasticities equal or smaller (in absolute value) than 0,4. When the two effects are combined, CHE incidence increases, meaning that reductions in the price of pharmaceuticals are not sufficient to countervail the changes in user charges, even with enlarged economic exemptions.

AbstractThis chapter presents a qualitative description of the scenario storylines for the REFLEX project. The scenario descriptions provide the overall qualitative framework for the modeling activities by setting-up two holistic socio-technical scenarios based on different storylines: the moderate renewable scenario (Mod–RES) as reference scenario and the (de-)centralized high renewable scenarios (High–RES) as ambitious policy scenarios. The chapter highlights the definition of main techno-economic framework parameters, macro-economic and societal drivers as well as of the considered political environment.

Management in NFV scenarios is a complex task. In this scenario, automated policy refinement can be used to enforce NFV-MANO functions to deal with the increased complexity. However, existing solutions do not perform policy analysis. Therefore, in this work, we propose a semantic model in OWL 2, named Onto-Planner, to assist the policy refinement process for NFV-MANO systems. Preliminary results show that Onto-Planner provides policy analysis when a DL reasoner is applied.

Abstract Autonomous driving has became one of the most hot trends in artificial intelligence area in recent years thanks to the machine learning algorithms. However, most of the autonomous driving studies are still limited to discrete action space. In this study, we propose to implement Deep Deterministic Policy Gradient algorithm for learning driving behavior over the continuous actions. For this purpose, a driving simulator is employed which interfaces with IPG CarMker software where the virtual environment and dynamical vehicle model can be built. “Human-in-the-loop” is performed in order to gather the data and a neural network which is implemented in Behavior Layer is trained to recognize two different scenarios-forward driving and stop. Based on the scenario the agent is dealing with, the actions are learnt and suggested from the DDPG algorithm. The experimental results show that DDPG algorithm is able to learn the optimal policy with continuous actions reliably for both scenarios.

There are three options for spent fuel management, recycle, once-through and wait and see. The national policy for spent fuel in Korea is “wait and see” and it has to be clearly decided for spent fuel management. The final disposal is the last stage of the fuel cycle and it is essential even though the recycling option will be chosen for spent fuel management policy. And the long-term strategy for spent fuel management considering safety and retrievability is needed. In this study, once-through fuel cycle was focused on for back-end fuel cycle. The international trend for SF management policy and the Korean situation has been investigated. The once-through back-end fuel cycle scenarios has been developed and screened in point of technical and economical aspect. The optimal scenario has been derived by relative comparison and the long-term SF management strategy has been proposed which satisfies both domestic conditions and international trends.

The task of real-time combat game is to coordinate multiple units to defeat their enemies controlled by the given opponent in a real-time combat scenario. It is difficult to design a high-level Artificial Intelligence (AI) program for such a task due to its extremely large state-action space and real-time requirements. This paper formulates this task as a collective decentralized partially observable Markov decision process, and designs a Deep Decentralized Policy Network (DDPN) to model the polices. To train DDPN effectively, a novel two-stage learning algorithm is proposed which combines imitation learning from opponent and reinforcement learning by no-regret dynamics. Extensive experimental results on various combat scenarios indicate that proposed method can defeat different opponent models and significantly outperforms many state-of-the-art approaches.

The Saudi agricultural sector relies on diesel for irrigation, which is provided to farmers at a much lower price than the average global price, implying significant opportunity costs. With the aid of soft-coupled power and macro-econometric models, we assess the cost and macroeconomic implications of electrifying irrigation activities in the Saudi agricultural sector. Three electrification scenarios are considered: electrifying each individual farm with a dedicated hybrid renewable micro-grid, electrifying the entire farm cluster with central generation and connecting the entire cluster via transmission to the national grid. Compared with the base-case, connecting the farm cluster to the national grid is found to be the most economical but the least environmentally friendly. The renewable and central generation scenarios are costlier (compared with the transmission scenario) due, respectively, to the high battery costs and gas infrastructure needed.

This report evaluates scope 3 emissions along the copper and iron ore value chains and the opportunities that Latin America and the Caribbean (LAC) has to become a low carbon metals and solutions hub. The report presents four carbon emission scenarios that represent different sets of decisions for policy-makers and investors. Two scenarios fall short of aligning with Paris targets: (1) the business as usual (BaU) scenario with no further abatement action; and (2) a BaU scenario with the current level of emission reduction potential from players in the value chain (BaU Possible). The other two scenarios deliver the required carbon reductions to be compliant with the Paris Agreement by 2060, but through different strategies: (3) the BaU Paris scenario. where alignment with Paris targets is achieved by keeping BaU volumes and reducing carbon intensity per tonne of metal; and (4) the Decoupled scenario, where carbon intensity reductions are relaxed and compensated by a reduction in primary supply to align the value chain emissions to a Paris trajectory. All scenarios require LACs leaders to consider investments in low-carbon technology in different degrees. The report argues that, given its competitive position in the cost curve for copper and iron ore and an abundance of enabling factors for low carbon strategies, the region could become a key source of low carbon metals and solutions as long as it is proactive in adopting all the necessary measures from public sector and industry perspectives. Finally, the report concludes that myriad opportunities exist for LAC, including new business models, technologies and products, and that these could yield a greater economic and social contribution to the region than the BaU trajectories.

This study conducted an economic analysis of future US forest mitigation potential using a detailed economic model of the global forestry sector. The scenario design included a wide range of possible future carbon price incentives and climate policy structures (unilateral and global mitigation). Results across all scenarios show US forest sector mitigation potential ranging from 54 to 292 MtCO2e between 2015 and 2030 (5 to 47 percent of the additional mitigation needed to achieve the 26 to 28 percent emissions reduction target). The results from this study suggest that the US forest sector can play an important role in global greenhouse gas mitigation efforts, including efforts to meet any potential future US mitigation targets.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

We study how policies that facilitate firm digital adoption shape the labor market and economic recovery from COVID-19 in a search and matching framework with firm entry and exit where salaried firms can adopt digital technologies and the labor market and firm structure embodies key features of Latin American economies. Using Mexico as a case study, we first show that the model quantitatively replicates the dynamics of the labor market and output at the onset of the COVID recession and in its aftermath, including the sharp decline in labor force participation and informal employment that is unique to the COVID recession. We then show that a policy-induced permanent reduction in the barriers to adopting digital technologies introduced at the trough of the recession bolsters the recovery of GDP, total employment, and labor income, and leads to a larger expansion in the share of formal employment compared to the no-policy scenario. In the long run, the economy exhibits a long-run reduction in total employment and labor force participation, but higher levels of GDP and labor income, greater average firm productivity, a larger formal employment share, and a marginally lower unemployment rate.

What is a ‘science superpower’? Sarah Main and Graeme Reid explore reactions to the term from stakeholders across the UK and examine alternative versions of a future in which ‘science superpower’ status is achieved. Their report is published today by the Foundation for Science and Technology. Jeremy Hunt, Rishi Sunak, Boris Johnson, George Freeman and other senior figures in government use the phrase ‘science superpower’ as a headline for ambitious, visionary science policy. It is a potent phrase but open to varied interpretation. By exploring scenarios in which the UK has achieved ‘science superpower’ status by different means, the authors stimulate debate about the desired characteristics of this status and highlight the choices facing policy-makers on the path to become a more research-intensive UK.