Academic literature on the topic 'Behavioral energy use'

Local, state, and federal governments are continuing to design and pass programs and policies to decrease demand for energy. These programs and policies provide social, economic, and environmental benefits. Social and behavioral scientists can inform policymaking and evaluation because of their expertise in behavioral change. Specifically, policies will be more effective if they include a behavioral level analysis to help select behaviors, design behavioral change strategies that target appropriate motives and abilities, and attend to social and environmental contexts. After describing these principles, the article illustrates how they can inform the evaluation of labeling programs designed to encourage energy-efficient behaviors among consumers, manufacturers, and building owners.

Abstract Objectives This study assessed energy drink consumption and high-risk behaviors, including alcohol and drug use, cross-sectionally among participants in three cohort studies—the Nurses’ Health Study 3 (NHS 3), the Growing Up Today Study (GUTS) and GUTS2. Methods Questionnaires, including validated food-frequency questionnaires (FFQs), collected participant demographics, risky behavior, and energy drink consumption data. [The specific question used for energy drink intake read as follows: “Do you drink energy drinks, e.g., Red Bull, Rock Star, Monster (8 oz. can)?” for NHS3, 2010–2019; GUTS, 2011; and GUTS2, 2011.] Following descriptive analysis, multivariable-adjusted logistic regression estimated associations between energy drink consumption and odds of risky behaviors, including pooled odds-ratios (pORs) across all cohorts. Results Of the 46,390 participants this study assessed, ∼13% reported energy drink consumption at least monthly. Risky behaviors associated with energy drink consumption included smoking [pOR: 1.88 (95% CI 1.55–2.29)], having higher body mass index [pORs: 1.31 (95% CI 1.11–1.53) for overweight (25–30 kg/m2) and 1.67 (95% CI 1.34–2.08) for obesity (≥30 kg/m2) compared to <25 kg/m2, respectively], insufficient sleep [pOR: 1.29 (95% CI 1.11–1.50) for <7 hours compared to 7–9 hours], tanning bed use [pOR: 2.31 (95% CI 1.96–2.72)], binge drinking [pOR: 2.53 (95% CI 2.09–3.07)], marijuana use [pOR: 1.49 (95% CI 1.28–1.73)], and use of any illegal drugs (other than marijuana) [pOR: 1.45 (95% CI 1.16–1.81)]. Demographic factors associated with consumption of energy drinks included higher education, which was associated with lower odds of energy drink consumption [pORs: 0.71 (95% CI 0.56–0.91) for bachelor's degree and 0.55 (95% CI 0.40–0.74) for master's degree, compared to no bachelor's degree, respectively], and race/ethnicity [pOR: 4.43 (95% CI: 2.41–8.15) comparing African Americans to non-Hispanic white]. Conclusions Both within and across the cohorts, risky behaviors were associated with higher odds of energy drink consumption. Funding Sources This study was funded via FDA contracts and NIH grants.

The current methods for simulating building energy consumption are often inaccurate, and the error could be as large as 150%. Various types of occupant behavior may explain this inaccuracy. Therefore, it is important to identify an approach to estimate the impact of the behaviors on the energy consumption. The present study used EnergyPlus program to simulate the energy consumption of the HVAC system in an office building by implementing a behavioral artificial neural network (ANN) model. The behavioral ANN model calculates the probability of behavior occurrence according to indoor air temperature, relative humidity, clothing level and metabolic rate. The probability was used to predict energy use in 20 offices for one month in winter, spring and summer in 2018, respectively. Measured energy data from the offices were used to validate the simulated results. When a behavioral artificial neural network (ANN) model was implemented in the energy simulation, the difference between the simulated results and the measured data was less than 13%. Energy simulation using constant thermostat set point without considering occupant behavior was not accurate. Our further simulations found that adjustment of thermostat set point and clothing level by occupants could lead to 25% and 15% energy use variation in interior offices and exterior offices, respectively.

Some species exhibit behavioral plasticity by altering their aggressive behavior based on their opponent. Atlantic spotted dolphins (Stenella frontalis) and bottlenose dolphins (Tursiops truncatus) are two sympatric species resident to the northern Bahamas. We examined whether groups of adult male spotted dolphins demonstrated behavioral plasticity during two different types of aggressive interactions. We described and compared the types of aggressive behaviors used during intraspecific aggression and interspecific aggression with bottlenose dolphins. Between the years 1991-2004, twenty-two aggressive encounters (11 intraspecific (spotted only), 11 interspecific (spotted vs. bottlenose)) were behaviorally analyzed. Twenty-three specific aggressive Behavioral Events, further grouped into three Behavioral Types, were examined throughout these encounters. Similarities and differences in the use of the Behavioral Types occurred during intra- and interspecific aggression. Groups of male Atlantic spotted dolphins altered their behavior during aggressive encounters with male bottlenose dolphins. Spotted dolphins increased their use of the Pursuit Behavioral Type and did not use the Display Behavioral Type significantly more than the Contact Behavioral Type during interspecific aggression. The increased use of a more overt and energy intensive Behavioral Type, Pursuit, suggests that Atlantic spotted dolphins altered their behavior during aggressive encounters with bottlenose dolphins to compensate during fights with a larger species and/or to effectively communicate with a different species.

Long-term pharmacologic strategies that may be used in conjunction with lifestyle changes to address the obesity epidemic have, until recently, been an unmet clinical need. Interestingly, pharmacologic interventions to date have not specifically focused on modifying the behavioral aspects of eating. Food intake is influenced by multiple pathways, including the homeostatic regulation of energy balance controlled by the hypothalamus and the mesolimbic reward system, dysregulation of which can lead to reward eating, food craving, and overconsumption of food. A growing body of evidence suggests that targeting the reward system can be a successful intervention for obesity management. Sustained-release naltrexone/bupropion is a novel combination therapy that targets both the hypothalamic melanocortin system and the reward system. In clinical trials, naltrexone/bupropion has been associated with sustained and clinically meaningful weight loss together with beneficial effects on eating behavior and improvements in cardiometabolic factors. Craving and control of food intake were also measured and correlated with improved outcome.

Complete overview of energy use in a residential building is depends on many different factors. When analyzing proper and effective ways for energy reducing/conserving systems, often times only technological solutions for households appliances are considered. Human behavior has been shown to be an important factor affecting the overall energy use in the household. Many aspects of energy use are directly connected to user behavior and are affected by how the user utilizes available systems. This paper focuses on describing the mean influencing causes of human environmental psychology based on study on a Swedish suburb community, called Fårdala. User behaviors and actions affecting residential energy use are analyzed and presented in form of eleven (11) abstract triggers to households energy use. Finally an energy monitoring system based on the findings are purposed. What is found from study on human psychology, shows that human behavior is mainly controlled by three (3) key categories of behavior. Conscious/voluntary behavior, Socio-environmental/cultural based behavior and Systemic/learned behavior. Out of the three, while the last one poses as most influential on behavior related energy use, it is also the hardest to affect and change. To effectively counteract the negative effects of user behavior on residential energy use, energy saving devices should react more accordingly to the users and offer engagement. Such a system is an energy monitoring device, which allows for a “double-sided” communication with the user. The user is presented with relevant information about real-time energy use of all of the systems and is able to make changes on the fly. The system should also be able to learn and apply energy saving actions based on user behavior.

Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 101-109).
Household in-home activities and out-of-home transportation are two major sources of urban energy consumption. In light of China's rapid urbanization and income growth, changing lifestyles and consumer patterns - evident in increased ownership of appliances and motor vehicles - will have a large impact on residential energy use in the future. The pattern of growth of Chinese cities may also play an intertwined role in influencing and being influenced by consumption patterns and, thus energy use. Nonetheless, models for evaluating energy demand often neglect the evolution of appliance & vehicle ownership and directly correlate consumption with static characteristics without explicit behavioral links. In this thesis I aim to provide a comprehensive method for understanding household energy behavior over time. Using household survey data and neighborhood form characteristics from Jinan, a mid-sized Chinese city, I explore the relationship between neighborhood design and household-level behaviors and their impact on final energy consumption. My ultimate goal is to provide the modeling engine for the "Energy Proforma©" a tool intended to help developers, designers, and policy-makers implement more energy-efficient neighborhoods. To predict in-home and transportation energy use, and their trade-offs, I develop an integrated household-level micro-simulation framework. The simulation tool is based on a total of eight inter-related behavioral models which estimate out-of-home energy use by predicting trip generation, mode choice and trip length for each household and in-home energy use according to different energy sources. In the various sub-models, relevant dimensions of neighborhood form and design are included as explanatory variables. These models are then combined with modules that update household demographics, appliance & vehicle ownership information, and activity trade-off patterns. These inter-linked models can then be used to estimate the long-term effects of neighborhood design on household energy consumption and greenhouse gas emissions. Unlike separate in-home or out-of-home energy demand models, I develop an integrated simulation framework for forecasting. It captures estimated trade-off effects between in-home and transportation energy-consuming behaviors. The approach produces indicators of detailed behavioral outcomes such as trip mode and trip length choice, making it easier to relate policies, such as mode-oriented strategies, to ultimate outcomes of interest. I ultimately aim to provide urban designers, developers, and policy makers a decision support tool to explore and compare long-term energy performance across proposed neighborhood development projects.
by Feifei Yu.
S.M. in Transportation

As the effects of global climate change become increasingly apparent, many concerned individuals are making efforts to reduce their greenhouse gas emissions. One simple and effective method of reducing one s personal carbon footprint is through energy conservation behavior. Studies have shown that occupant behavior can control as much as 50% of residential energy use and that energy use varies widely between residences with the same number of occupants depending on consumption behavior. In light of this, energy conservation behavior is a valuable method of reducing greenhouse gas emissions and curbing the effects of climate change. Motivating people to conserve energy could have profound positive effects on the environment. The following study applies Icek Ajzen s Theory of Planned Behavior (1991) to energy conservation behavior among college students in the state of Florida. This research tests the hypothesis that pro-environmental attitudes, influence of peers, and a high level of perceived control over behavior have a significant impact on energy conservation behavior.
M.A.
Department of Sociology
Sciences
Applied Sociology MA

Research on interventions aimed to promote energy savings has shown support for direct feedback using in-home displays (IHDs) to reduce energy consumption. These displays are electronic devices that provide real-time energy information and are emerging as an effective tool to communicate with people about their energy consumption. How feedback is presented to people and how they understand the meaning of such feedback largely depends on the design of the display, yet there are relatively few studies that investigate the way in which the display can best be designed to present energy information and motivate energy-saving behaviour. Further, even though there is a wide range of variations in the visual presentation of feedback, there is a lack of focus on the process of optimising the IHD design. This thesis aims to address the need for designing IHDs at the display component level, by examining three types of display design (numerical displays, analogue displays using speedometer dials, and ambient displays using emotional faces) in both laboratory-based computer-simulated experiments and field-based experiments: participants’ abilities to detect changes in energy information shown on the computer-simulated displays were measured by means of accuracy rate and response time, and their subjective preferences for display types were assessed against experimental data; live energy data were displayed using the three design types in a student residence at the University of Bath to see how they would influence energy-use behaviour. Results from the laboratory experiments demonstrated that both accuracy rate and response time for seeing changes in the information displayed were strongly associated with the type of display design. Participants preferred numerical display and were better at detecting changes in information with this display than with the other two. Conversely, the student residence experiments showed that when participants’ attention was divided in a household setting, there was no difference in energy consumption among experimental groups who received information from any of the three display types. However, these experimental groups used significantly less energy compared with control groups, who had no displays installed. It was concluded that 1) the mere presence of a display device could influence people’s behaviour, regardless of the type of display design, people’s preferences or the level of user engagement with the display, although there was a strong indication that the ambient design worked better than the other two designs at an arbitrary statistical significance level of 0.95, and 2) subjective preferences and computer-simulated studies are poor guides to the actual performance of IHDs in real-world settings. This work helps establish how IHDs can be designed and the influence that they may have on people’s energy-consumption behaviour. It also contributes to the literature of exploring people’s perceptibility of energy information. The method used is replicable and can be applied in similar studies on energy display design. Lastly, the improved understanding gained through this work will facilitate the development of effective smart meter display technology that may help people adopt conscious energy behaviour in the long term.

This thesis focus on the free rider problem, well known in the field of economics. It is an unwanted situation that gives rise to unnecessary deadweight costs. The aim of this thesis is to analyse the free rider problem that occur when rent include housing utilities and especially when electricity is billed collectively. A Difference-in-Differences design has been applied on two different sets of panel data covering tenants electricity consumption. The results show that tenants use 21.3 percent more electricity when not paying directly for their own electricity consumption. This thesis also shed some light on different components of this problem. The findings in this thesis contributes to the limited research in this field with new empirical evidence.

Predator-prey interactions form an essential part of ecological communities, determining the flow of energy from autotrophs to top predators. The rate of predation is a key regulator of that energy flow, and that rate is determined by the functional response. Functional responses themselves are emergent ecological phenomena – they reflect morphology, behavior, and physiology of both predator and prey and are both outcomes of evolution and the source of additional evolution. The functional response is thus a concept that connects many aspects of biology from behavioral ecology to eco-evolutionary dynamics to food webs, and as a result, the functional response is the key to an integrative science of predatory ecology. In this book, I provide a synthesis of research on functional responses, starting with the basics. I then break the functional response down into foraging components and connect these to the traits and behaviors that connect species in food webs. I conclude that contrary to appearances, we know very little about functional responses, and additional work is necessary for us to understand how environmental change and management will impact ecological systems

Tis chapter explains the famous equation E = mc2 as part of a wider relationship between energy, mass, and momentum. We start by defning energy and momentum in the everyday sense. We then build on the stretching‐triangle picture of spacetime vectors developed in Chapter 11 to see how energy, mass, and momentum have a deep relationship that is not obvious at everyday low speeds. When momentum is zero (a mass is at rest) this energy‐momentum relation simplifes to E = mc2, which implies that mass at rest quietly stores tremendous amounts of energy. Te energymomentum relation also implies that traveling near the speed of light (e.g., to take advantage of time dilation for interstellar journeys) will require tremendous amounts of energy. Finally, we look at the simplifed form of the energy‐momentum relation when the mass is zero. Tis gives us insight into the behavior of massless particles such as the photon.

Understanding the use-phase energy consumption of consumer electronics is of great importance, as it has significant effects on both policy and product designs. Inaccurate estimations of the use phase energy consumption can offset the results of the life cycle assessment and impeach the effectiveness of the energy intervention policies. The use phase energy consumption is governed by the consumers’ usage behavior. However, the relationship between consumers’ attributes and their usage behavior, and energy consumption is not clear. This paper analyzes two data sets, a data set of hard drives’ Self-Monitoring, Analysis and Reporting Technology (S.M.A.R.T) and the Residential Energy Consumption Survey (RECS) to shed light on the relationship between usage behavior and energy consumption. Several supervised and unsupervised machine-learning methods have been used to reveal possible trends in the consumers’ use-phase attributes. The results of the study suggest that various demographic properties and behavioral variables related to computer usage affect the energy consumption profile of households.

Within the commercial sector, energy managers and building operators have a large impact over their organizations’ energy use. However, they mostly focus on technology solutions and retrofits, rather than human or corporate behaviors, and how to change them. This gap in targeted commercial sector research and behavioral interventions provides a great opportunity which is currently not being addressed. This paper presents a field research pilot where an empirical behavior change research process was applied and taught to commercial energy users in Ontario, Canada. This course served to fill an identified market gap and to improve commercial energy managers’ literacy in behavioral science theory and techniques. A needs assessment identified a clear gap in behavioral training for energy managers, and high interest in the course further proved out the market opportunity for professional training on how to design, implement and evaluate behavior change interventions. Evaluation results identified positive feedback in terms of course reaction, self-reported learning and behavioral outcomes, and tangible results when course participants returned to work to apply their learnings. Evaluation results suggest that such training fills a vital gap in the current Strategic Energy Management (SEM) landscape, and could unlock significant savings in the commercial energy sector.

Abstract Substantial energy savings during the use phase of internal-combustion and electric automobiles can be achieved by increasing eco-driving behavior, particularly reduced acceleration and braking. However, motivating widespread adoption of this behavior is challenging, with obstacles including incompatibility with drivers’ values and priorities, and disassociation between drivers’ actions and observable consequences. Efforts focused on informational approaches, e.g., training programs and educational campaigns, are both difficult to scale up and largely ineffective, with drivers reluctant to make long-term changes. Alternatively, behavior can be influenced by redesigning the context within which the behavior occurs. Such an intervention must be effective across demographics and underlying behaviors to achieve ubiquity. The current study investigates the perceived effect on driving style of a simple graphical dashboard display depicting an animated coffee cup. This display incorporates associative mental models and contextual relevance to increase the salience of inefficient vehicle movements and nudge drivers to adopt a smoother driving style. An online Amazon-Mechanical-Turk survey with 92 participants revealed a significant preference for the coffee cup over two other displays when controlling for demographic variables. This result offers preliminary evidence suggesting that greater success at promoting eco-driving may be achieved by using a behavioral nudge.

Energy efficiency (EE) program administrators and policy makers have long encouraged the adoption of efficient technologies and conservation practices across all energy users and sectors. Energy users who haven’t yet participated in efficiency and conservation programs despite ongoing outreach are often referred to as “Hard-to-Reach” (HTR). These individuals or organizations can include, for instance, low income or rural audiences on the residential side and small businesses or building operators on the commercial side. More effectively engaging underserved and HTR audiences is key to ensuring everyone benefits equitably from efficiency and conservation interventions. In June 2019, energy efficiency, behavior change and HTR researchers, practitioners, and policy makers from five countries embarked on a 3-year project in partnership with the UserCentred Energy Systems Technology Collaboration Programme (Users TCP) by the International Energy Agency (IEA). The purpose of this effort is to characterize the diverse audience segments commonly referred to as HTR and to uncover the barriers and behavioral opportunities to more effectively engage them. This paper describes the first of these efforts. We have synthesized data from a global survey (N=110) and stakeholder interviews with 40+ energy efficiency experts striving to better understand and engage HTR in their respective countries. This paper provides initial insights from this data into how HTR energy users are defined across the world and which segments have been prioritized globally for focused outreach. The overarching goal is to use a standardized research process to inform and improve how energy efficiency, behavior change, and demand response programs targeting specific HTR audiences are designed, implemented and evaluated.

Energy efficiency (EE) program administrators and policy makers have long encouraged the adoption of efficient technologies and conservation practices across all energy users and sectors. Energy users who haven’t yet participated in efficiency and conservation programs despite ongoing outreach are often referred to as “Hard-to-Reach” (HTR). These individuals or organizations can include, for instance, low income or rural audiences on the residential side and small businesses or building operators on the commercial side. More effectively engaging underserved and HTR audiences is key to ensuring everyone benefits equitably from efficiency and conservation interventions. In June 2019, energy efficiency, behavior change and HTR researchers, practitioners, and policy makers from five countries embarked on a 3-year project in partnership with the UserCentred Energy Systems Technology Collaboration Programme (Users TCP) by the International Energy Agency (IEA). The purpose of this effort is to characterize the diverse audience segments commonly referred to as HTR and to uncover the barriers and behavioral opportunities to more effectively engage them. This paper describes the first of these efforts. We have synthesized data from a global survey (N=110) and stakeholder interviews with 40+ energy efficiency experts striving to better understand and engage HTR in their respective countries. This paper provides initial insights from this data into how HTR energy users are defined across the world and which segments have been prioritized globally for focused outreach. The overarching goal is to use a standardized research process to inform and improve how energy efficiency, behavior change, and demand response programs targeting specific HTR audiences are designed, implemented and evaluated.

Climate change is often considered in terms of its macroscale implications. For example, many governments and non-governmental organizations are engaged in the development of policy frameworks that could influence different societal actions and behavioral scenarios. But such macroscale policy decisions may also significantly impact the localized design of products and services in different business ecosystems. Unfortunately, products and services are generally designed only taking into account local influences. An approach that ties macroscale frameworks to localized product- or system-level design metrics is lacking. For example, the cost of upgrading the entire U.S. electrical system has been estimated to be on the order of $200 billion, and recent U.S. policy discussions in the area outline options such as “smart” grid upgrades, distributed and/or on-site renewable energy systems including solar and wind energy, infrastructural support for plug-in of electric and hybrid vehicles etc. But most existing electricity generation and thermal performance models of power generating stations or cogeneration plants fail to provide any indication of the environmental impacts associated with distributing electricity from generator to point-of-use. It is thus not intuitive how the direction of localized plant or system design should be altered given the different macro-level initiatives. This paper attempts to fill this gap by exploring a methodology that combines engineering economics, probabilistic risk assessment, and thermodynamic (2nd Law) analysis to evaluate different policy choices. Specifically, a framework that could allow quick estimation of the comparative consumption, operational power requirements, relative thermal performance and environmental footprint associated with different proposals on upgrading the grid is developed. The approach is demonstrated in the context of a representative segment of a hypothetical electrical grid distribution system located between two electric power generating stations (EPGS) facing overload as additional customer demands are projected to be integrated with renewable sources in the near-term future.

In a country like France, electricity consumption devoted to domestic lighting represents nearly a fifth of the total energy consumption of a building. The use of electric lighting is influenced by several factors such as the building’s structural characteristics, the activities of its occupants, the lighting equipments, and the level of natural light. Designers do take into account, in their energy models, the influence of occupants on the building’s overall energy consumption. However, these models still have some drawbacks regarding the comprehension of real “occupants’ energy behaviors” which play an important role in the discrepancies between predicted and real energy consumptions. The behavioral factors behind occupants’ usage trends of energy are still not thoroughly explored. Therefore, it is assumed that a better comprehension of these behaviors and consumption mechanisms could lead to the identification of technical solutions and energy saving potentials, thus resulting in a more robust building design. The present paper aims to provide an insight into domestic lighting usages. The main objective is to explore the key factors (socio-demographic, economic, technical and behavioral) responsible for the disparities in lighting consumption between one household and another. For this purpose, an experiment is performed concurrently to the proposal of a lighting usage model. A micro level investigation protocol is elaborated and used to conduct in-depth studies on the usage patterns of electric lighting. The survey is conducted on a sample of 8 French households. The methodology for constructing the experimental protocol, its deployment, as well as the results obtained and their analysis are presented in this paper. The need for further qualitative and quantitative studies to better understand the usage trends of electric lighting is discussed.

This short pedagogical movie illustrates an effect in nuclear physics called backbending which was first observed in the study of the rotational behavior of rapidly rotating rare-earth nuclei in Stockholm, Sweden in 1971. The video contains a mechanical analog utilizing rare-earth magnets and rotating gyroscopes on a turntable along with some historic spectra and papers associated with this landmark discovery together with its explanation in terms of the Coriolis induced uncoupling and rotational alignment of a specific pair of particles occupying high-j intruder orbitals. Thus backbending represents a crossing in energy of the groundstate, or vacuum, rotational band by another band which has two unpaired high-j nucleons (two quasi-particles) with their individual angular momenta aligned with the rotation axis of the rapidly rotating nucleus. Backbending was a major surprise which pushed the field of nuclear structure physics forward but which is now sufficiently well understood that it can be used as a precision spectroscopic tool providing useful insight for example, into nuclear pairing correlations and changes in the latter due to blocking effects and quasi-particle seniority, nuclear deformation, the excited configurations of particular rotational structures and the placement of proton and neutron intruder orbitals at the Fermi surface.

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%.