Academic literature on the topic 'Investment decision support'

Rapid development of financial markets resulted new challenges for both investors and investment issues. This increased demand for innovative, modern investment and portfolio management decisions adequate for market conditions. Financial market receives special attention, creating new models, includes financial risk management and investment decision support systems.Researchers recognize the need to deal with financial problems using models consistent with the reality and based on sophisticated quantitative analysis technique. Thus, role mathematical modeling in finance becomes important. This article deals with various investments decision-making models, which include forecasting, optimization, stochatic processes, artificial intelligence, etc., and become useful tools for investment decisions.

Individual investments behaviour is concerned with choices about purchases of small amounts of securities for his or her own account. Decision tools often support investment decisions. It is assumed that information structure and the factors in the market systematically influence individuals’ investment decisions as well as market outcomes. Decision tools often support investment decisions. It is assumed that information structure and the factors in the market systematically influence individuals’ investment decisions as well as market outcomes. Investor market behaviour derives from psychological principles of decision making to explain why people buy or sell stocks. These factors will focus upon how investors interpret and act on information to make investment decisions. The purpose of the study was to identify the factors that influence investment decision making among potential individual investors in Malaysia. Three behavioural factors might influence investment decision making which are accounting-information, firm-image coincidence and personal-financial-needs. A set of questionnaire was distributed to 384 potential investors in Malaysia specifically in housing area of Klang Valley as population of this study. Based on the findings, it showed that there is positive relationship between accounting-information, firm-image-coincidence and personal-financial-needs in investment decision making. Hence, between these three behavioural factors, accounting-information, firm-image coincidence and personal-financial-needs, the main influential factor is accounting-information. This study also proposed a future research for investment decision making and give implications to the potential investors, community, organization, policy makers and investment practitioners.

Investment is the placement of a number of funds at this time with the hope of obtaining benefits in the future. Stocks are one of the most popular investments. The current millennial generation is interested in investing in stocks because the capital required is not too large. However, in choosing a good stock for investment, the ability to read financial ratios is required. Errors in reading financial ratios will cause stock investment not to go as expected. To help with this, a system capable of supporting decisions is needed. There are several methods that can be used to produce a decision support system. In this study, the authors use the Capital Asset Pricing Model (CAPM) method in designing a decision support system in stock investment selection.The method in this research is through observation, interview, and literature study. The system design is made using Contex Diagram, HIPO, DAD, and database design. The system is made in a program with the PHP programming language. The process of determining the selection of stock investments using the Capital Asset Pricing Model (CAPM) method can simplify the determination process. Then with the method. can make it easier to determine the selection of stock investment.The final result in the stock investment selection process is a report that states investment (Ri> E) or not investment (Ri <E).

The evaluation of real estate assets is currently one of the main focal points addressed by territorial marketing strategies, with the view of developing high-performing or competitive cities. Given the complexity of the driving forces that determine the behavior of actors in a real estate market, it is necessary to identify a priori the factors that determine the competitive capacity of a city, to attract investments. The decision support system allows taking into account the key factors that determine the “attractiveness” of real estate investments in competitive urban contexts. This study proposes an integrated complex evaluation model that is able to map out and encapsulate the multidimensional spectrum of factors that shape the attractiveness of alternative real estate options. The conceptual–methodological approach is illustrated by an application of the model to a real-world case study of investment choice in the residential sector of Naples.

Purpose – The tightening competition and performance pressure in companies often leave no time or space for the assessment of business impacts of different investments and projects. In addition, in many cases the assessment may be challenging and there is no experience available to undertake it. Despite that companies often commit to different projects and investments without careful planning and vision of the costs it may cause. The purpose of this paper is to create a decision support system in order to facilitate and increase the assessment of business impacts of different investments concerning to machine-to-machine (M2M) systems. Design/methodology/approach – The created decision support system is composed of cost-benefit analysis including several investment decision methods. In order to deepen the understanding on it, the system was applied to two cases from the M2M business. Findings – During the study it was found that different financial metrics might give contradictory results when deciding whether to undertake an investment. In addition, a significant finding was how much some variables may have significance to the eligibility of an investment than others. The study also gave understanding how long payback time can be and how risky the investments might be in different M2M applications. Originality/value – The study describes the created decision support system and it is applied to two different M2M applications. The system provides a comprehensive combination of different financial metrics, which will help any manager make decisions whether an investment is eligible or not.

While it is widely agreed that contemporary computer security is insufficient to meet the challenges faced, the remedies for its failures are far less obvious. Vast resources have been placed into technical solutions to little effect, prompting some to employ the constructs of economics to frame this problem as one to be 'managed', rather than 'solved'. However, to date economically-inspired decision support approaches have focused disproportionately on post-deployment security investment. With the preponderance of security issues stemming from the introduction of vulnerabilities during design and development, models that span the system development lifecycle are essential to efficiently address the root of many security issues. In addition, the need to impact system security at a fundamental level requires integration with existing security-development processes and standards. This dissertation presents an approach to secure software development that is derived from an economically-inspired understanding of security. After demonstrating how existing security guidance can give rise to inefficient decisions, models for security investment are developed that incorporate investments made in software security during system inception and development relative to those made during deployment and operations. By employing these models, conditions are identified whereby software security improves the return on (security) investment, and provide theoretical and empirical evidence to support the adoption of software security. This is followed by an exploration of how economic considerations can drive existing secure software engineering processes, culminating in a case study that illustrates the application of these principles to an ongoing system development effort.

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters’ performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.

In the recent years, ongoing debates in the mineral sector has shown that efficient use of natural resources is of vital importance as the use of minerals is essential for modern living. Especially, in the context of sustainable development, it is required that mineral resources should be exploited to maximize the contribution to the well being of current generation without depriving the potential for future generations to meet their own needs. The aim of this thesis is to develop a decision support system using system dynamics methodology where

The aim of this thesis is to provide to the governmental decision-maker/user, an instrument that can assist him/her in improving the infrastructure investment decision in the economical, environmental and sustainable aspects. This means that, the Return on Investment (ROI) of the concerned transport infrastructure, satisfying environmental and sustainable constraints must be positive, and corresponding to an optimal investment cost. The decision support system can be applied in two dimensions. One dimension is where the real negotiation process is occurring between private and public stakeholders, called “real time negotiation process”. The second dimension is where the negotiation process is impelled by the user (public part) without private stakeholders interaction (but with interaction through simulation), called “virtual negotiation process”. The simulation and local optimization techniques, in phase with agent technology, used in the “virtual negotiation process” enable us to achieve a certain amount of alternative decisions to the primary/suggested decision to be evaluated. The CommonKADS methodology with mathematical modeling, and agent technology have been the support respectively for extracting and implementing the knowledge in the domain, monitoring, automating and updating the decision process. The principle of “Joint logistic” [1] in my effort concerns by the means of sharing financial and information resources; This leads to the empowerment of the supply chain feedbacks (roles), involved in the earlier stages of public transport decision making-process. It appears that within the decision-making process, the government is often dealing with the conflicting objectives, while interacting with the business stakeholders. For instance, the estimated investment cost of a specific transport infrastructure can exceed the income generated by this infrastructure, thus the ROI of the concerned transport infrastructure (TI) will be negative. From this perspective the government faces three choices: a) increase the rate of the taxes applied on that transport infrastructure or any other taxes, in order to make ROI positive, this can be matter of discussion/disagreement for the business community b) reduce the investment cost which means suggest a different TI with a lower quality standard compared to the previous; this can also be a matter of disagreement between the two concerned stakeholders. c) delay of the investment in the specific transport infrastructure. In fact in the most situations the government uses the first approach, which effects might be consequently unpredictable and disastrous in the economical and environmental sense for the government. From this point of view my attempt is to propose an intelligent decision support system for governments or project groups (e.g. East West project group), involving conceptually as components web portal, database, simulator and knowledge base, that bases on an approach, that enables this negotiation/information exchange at the earlier steps of decision-making situation. This is concretized by gathering in real time accurate and relevant information from the private sector; furthermore the knowledgebase of the designed system is conceived via the experience and historical knowledge of the concerned experts in the domain.
Please contact me via email : yjeanyv@hotmail.com or phone: +224 64 97 43 79

The National Health Service (NHS) is recognised as the largest public sector institution in Europe. This presents significant challenges in regards to operation and maintenance of the diverse built estate, and the ever-evolving clinical models of care. The economic downturn, and strict policy of austerity in the UK, presents limitations and challenges in capital investment. The majority of healthcare facilities which will be used throughout the 21st century, have already been built. This demands that solutions be found in the areas of asset maintenance and refurbishment. These challenges are complicated further, by the institutional and statutory requirements of the NHS to meet demanding sustainability targets. This in turn, is underpinned by exacting assessment methodologies and rating systems, and critically, an institutional ‘duty’ to pursue and evidence that ‘Value for Money’ has been achieved as far as reasonably practicable. The existing estate management tools were assessed by a process of triangulation, and the relevant decisionmakers and stakeholders from both the NHS and the Design Teams and Constructors were identified. The original contribution demonstrates the development of a novel decision support prototype which facilitates and improves the current decision making process. The prototype allows the integrated team to consider, evaluate, and agree, best-fit options in a measured, recordable, and replicable manner. Key to this process, is the ability to compare and rank often competing criteria, and to test the nonfinancial, and financial preferences by means of sensitivity analysis techniques. The research and the developed working prototype, were then tested and validated against an expert panel, on a broad scope of issues, ranging from Graphical User Interface aesthetics and usability, to functionality and applicability to the current standard business case process. The results of the testing and validation excercises were overwhelmingly positive.

Advances in microprocessor and communications technologies are making it possible to deploy advanced traffic signal controllers capable of integrating emergency vehicle preemption and transit priority operations. However, investment planning for such an integrated system is not a trivial task. Investment planning for such a system requires a holistic approach that considers institutional, technical and financial issues from a systems perspective. Two distinct service providers, fire and rescue providers and transit operators, with separate operational functions, objectives, resources and constituents are involved. Performance parameters for the integrated system are not well defined and performance data are often imprecise in nature. Transportation planners and managers interested in deploying integrated emergency vehicle preemption and traffic priority systems do not have an evaluation approach or a common set of performance metrics to make an informed decision. There is a need for a simple structured analytical approach and tools to assess the impacts of an integrated emergency vehicle preemption and transit priority system as part of investment decision making processes. This need could be met with the assistance of a decision support system (DSS) developed to provide planners and managers a simple and intuitive analytical approach to assist in making investment decisions regarding emergency vehicle preemption and transit signal priority. This dissertation has two research goals: (1) to develop a decision support system framework to assess the impacts of advanced traffic signal control systems capable of integrating emergency vehicle preemption and transit signal priority operations for investment planning purposes; and (2) to develop selected analytical tools for incorporation into the decision support system framework. These analytical tools will employ fuzzy sets theory concepts, as well as cost and accident reduction factors. As part of this research, analytical tools to assess impacts on operating cost for transit and fire and rescue providers have been developed. In addition, an analytical tool was developed and employs fuzzy multi-attribute decision making methods to rank alternative transit priority strategies. These analytical tools are proposed for incorporation into the design of a decision support system in the future.
Ph. D.

Today's society is characterized by a high degree of change where the manufacturing systems are affected by both internal and external factors. To adapt to current manufacturing requirements in the form of short lead-time, more variants, low and fluctuating volumes, in a cost-efficient manner, new approaches are needed. As the global market and its uncertainties for products and its lifecycles change, a concept called 'reconfigurable manufacturing system' has been developed. The idea is to design a manufacturing system for rapid structural change in both hardware and software to be responsive to capacity and functionality. A company's development towards the concept is often based on a strategy of incremental investments. In this situation, the challenges are to prioritize the right project and maximize the performance as well as the financial efficiency of a multi-approach problem. The report is based on three different issues. Partly how to standardize relevant performance-based metrics to measure current conditions, how new performance-based metrics can be developed in collaboration with reconfigurability characteristics, and set a direction for how decision models can be used to optimize step-based investments. The study is structured as an explorative study with qualitative methods such as semi-structured interviews and document study to get in-depth knowledge. Related literature addresses concepts in search areas such as reconfigurable manufacturing system, key performance indicators, investment decisions, and manufacturing readiness levels. The findings are extracted from interviews and document studies that generate a focal company setting within the automotive industry, which acts as the foundation for further analysis and decisions throughout the thesis. The analysis results in sixteen performance measurements where new measures been created for product flexibility, productionvolume flexibility, material handling flexibility, reconfiguration quality and diagnosability using reconfigurability characteristics. A conceptual decision support model is introduced with an underlying seven-step investment process, analyzing lifecycle cost, risk triggered events in relation to cost, and performance measurements. The discussion chapter describes how different approaches are used during the project that has been revised by internal and external factors. Improvement possibilities regarding method choice and the aspects of credibility, transferability, dependability, and conformability are discussed. Furthermore, the authors argue about the analysis process and how the result has been affected by circumstances and choices. The study concludes that a three-pronged approach is needed to validate the investment decision in terms of system performance changes, cost, and uncertainty. The report also helps to understand which performance-based metrics are relevant for evaluating manufacturing systems based on operational goals and manufacturing requirements.

The article examines and develops the methodological and methodological basis of corporate finance management in the context of their strategic development, when investment and financing decisions are particularly relevant from the point of view of determining acceptable risks and the financial well-being of the corporation. The conceptual and methodological foundations of analytical support for corporate finance management are developed, based on the definition of investment policy, its implementation through investment business planning and identification and assessment of financial risks in the framework of achieving strategic goals related to the modernization of Russian corporations. The ways of improving the quality of the corporate finance management strategy based on the introduction of budgeting technology and the use of controlling the implementation of the corporation's financial strategy are proposed. It is intended for postgraduates, undergraduates, university teachers, researchers and practitioners, full-time and part-time students studying in the areas of "Economics", "Management", "Finance and Credit" (master's level), as well as anyone interested in the problems of strategic management of corporate finance.

Within most pipeline organizations, maintenance and other facility departments use a range of separate data sources and applications to manage the integrity, maintenance and safety of their pipelines. These databases represent a significant investment over many years and are an integral part of day-to-day operations. It is evident that integration of data into a single, coherent data management system can provide significant benefits. However, the cost of implementing entirely new systems — with intensive data capture programs — is difficult to justify given the earlier investments. As a result, dedicated risk management software using static and separately maintained data is often used as a quick, low cost alternative to meet regulatory compliance commitments. Experience has shown that, with the right technology and an understanding of the specific needs of an organisation, a phased approach to integrated data management can be achieved at minimum initial cost by exploiting legacy data. This provides a low cost yet scalable solution that can grow with the changing needs of the business. In addition to the benefits of legacy data integration, this paper presents an insight into the additional benefits of technologies for distributed data access to provide simple, process-focussed reporting tools. The key role of data management in risk assessment and consequent integrity decision support process is discussed.

The Pentagon has a wide range of research and development programs using autonomy and AI in unmanned vehicles and systems, information processing, decision support, targeting functions, and other areas. This policy brief delves into the details of DOD’s science and technology program to assess trends in funding, key areas of focus, and gaps in investment that could stymie the development and fielding of AI systems in operational settings.

Within Task 64/IV Solar Process Heat, Subtask E Guideline to Market is aiming to support a wider penetration of solar thermal technologies in the supply of heating (and cooling) in industry, demonstrating Solar Heat for Industrial Processes (SHIP) to be an important contribution to the decarbonisation of the industrial sector. This requires not only to overcome technical and/or technological barriers, but it is crucial to also address on technical barriers. Whereas well suited system integration strategies, design tools, standardized procedures or modular components are all in all paramount for the development of reliable and prompt off the shelve solutions, experience shows that often non-technological barriers might have a critical role in the decision making process. Above all, competitiveness and investment/financing related barriers prove in many cases to be the bottleneck for the adoption of solar thermal technologies in the industrial framework.

Programs increasingly use community-based girl groups (CBGGs) to address risks and empower adolescent girls, but evidence on their impact is not always accessible to decision makers. A closer look at 30 CBGG programs in low- and middle-income countries found that CBGGs had the greatest reported success in improving health and gender attitudes and beliefs, while their effect on health behavior and status is mixed. Program implementers should consider CBGGs as a way to facilitate girls’ empowerment, with complementary measures to engage community members and to promote enabling environments for greater program impact. Increased interest and investment in CBGGs should be supported by greater investment in further research to bolster the evidence base.

Chinese-sponsored Economic and Trade Cooperation Zones offer African countries opportunities for new sources of investment, employment, skills transfer and technology transfer that promote industrialisation. For more than 15 years, these economic zones have provided a window into the complexities of transforming African aspirations for industrialisation into realities. Through policy frameworks and incentives, Chinese firms have been encouraged to link with local economies. Despite varied outcomes, African support for industrial parks remains strong. To be sustainable, African Special Economic Zones need constructive partnerships and strong African governance, backed by high-quality data to inform both Chinese and African government decisions.

This technical note encompasses Haiti's gender assessment, evaluates the success of gender specific actions implemented between 2011-2017, and presents a Gender and Transport Action Plan (GAP). The GAPs main aim is to guide investments in Haiti's transport sector in conceptualizing and designing gender-sensitive transport projects. By proposing specific gender actions and outcomes, the GAP establishes a clear path to integrate a gender dimension into operations design, implementation and, monitoring and evaluation. The GAP presents an overall plan to support the development of Haitian women. However, it focuses in the needs of women as transport services users and devotes specific attention to two female sub-groups, comprised by Haitian women engaged in informal trade of local and regional products. These women are known as Madan Sara (MS), and local female mango producers and traders (MPT). The decision of focusing on MS is related to their vital role in the Haitian local labor market and the peculiarity of their work, which has specific transport needs. Understanding and addressing these female groups transport constrains could strategically improve the outcomes of upcoming transport investments and bring more benefits to its beneficiaries.

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%.

This Technical Note describes the ecosystem service model data packets which were developed through the Integrated Economic-Environmental Modeling (IEEM) Platform project to facilitate the application of ecosystem services modeling to support evidence-based public policy and investment decision making. The data packets provide the spatial data and lookup tables needed to run the InVEST carbon storage, annual water yield, sediment delivery ratio, and nutrient delivery ratio models for 21 countries (and counting) in the Latin American and the Caribbean region. This Technical Note describes the content and structure of the data packets, model specific considerations, the alignment of land cover data for use in InVEST lookup tables, the customization of model parameters, and best practices in the application of the data packets.