Academic literature on the topic 'Percentage convergence'

Reliability assessment is a needed assessment in today's world. It is required not only for system design but also to ensure the power delivered reaches the consumer. It is usual for fault to occur, but it is best if the fault can be predicted and the way to overcome it can be prepared in advance. Monte Carlo simulation is a standard method of assessing reliability since it is a time-based evaluation that nearly represents the actual situation. However, sequential Monte Carlo (SMC) typically took long-time simulation. A convergence element can be implemented into the simulation to ensure that the time taken to compute the simulation can be reduced. The SMC can be done with and without convergence. SMC with convergence has high accuracy compared to the SMC without convergence, as it takes a long time and has a high possibility of not getting accurate output. In this research, the SMC is subjected to five different convergence items to determine which converge simulation is the fastest while providing better performance for reliability evaluation. There are two types of convergence positions, namely input convergence and output convergence. Overall, output convergence shows the best result compared to input convergence.

<span lang="EN-US">Reliability assessment is a needed assessment in today's world. It is required not only for system design but also to ensure the power delivered reaches the consumer. It is usual for fault to occur, but it is best if the fault can be predicted and the way to overcome it can be prepared in advance. Monte Carlo simulation is a standard method of assessing reliability since it is a time-based evaluation that nearly represents the actual situation. However, sequential Monte Carlo (SMC) typically took long-time simulation. A convergence element can be implemented into the simulation to ensure that the time taken to compute the simulation can be reduced. The SMC can be done with and without convergence. SMC with convergence has high accuracy compared to the SMC without convergence, as it takes a long time and has a high possibility of not getting accurate output. In this research, the SMC is subjected to five different convergence items to determine which converge simulation is the fastest while providing better performance for reliability evaluation. There are two types of convergence positions, namely input convergence and output convergence. Overall, output convergence shows the best result compared to input convergence.</span>

The purpose of this study is to analyze labor productivity inequality and labor dualism in Bengkulu Province. The method used is descriptive analysis, equipped with class typology and elasticity of employment. We are using employment data from BPS publications. The results show that by dividing business fields into 17 sectors in 2018 and 2019, labor productivity inequality is awfully unequal, which is indicated by a very high standard deviation rate. Meanwhile, labor dualism is led by informal workers by a percentage of over 60%. More workers with primary education are absorbed in the informal sector, whereas educated workers are mostly taken in the formal sector. The highest coefficient of labor absorption elasticity for legal workers occurred in 2016 (3.14) and for informal workers in 2015 (1.73).Keywords: labor dualism, labor productivity

Fourth roots of the natural numbers from 1 to 30 have been calculated by Bisection method inthe interval [0, 3] using stopping tolerance 0f 0.00001. Calculated roots have been comparedwith the actual values of roots to obtain error and percentage error in the calculated roots.Numerical rate of convergence has also been calculated in the determination of each fourthroot. The highest numerical rate of convergence of Bisection method has been observed in thecalculation of fourth root of 2 and is equal to 1.754385964912. The lowest numerical rate ofconvergence of Bisection method has been observed in the calculation of fourth roots of 1, 3,4-8, 10, 12 and is equal to 1.333333333333. Average error, average percentage error and averagenumerical rate of convergence of Bisection method have been found to be 0.000000062635,0.000003048055 and 1.458082183940 respectively

The method of false position has been applied to calculate the fourth roots of the naturalnumbers from 1 to 30 in the interval [0, 3] with the stopping tolerance of 0.00001 using C++computer program. The minimum error 0.000000029282 and minimum percentage error0.000001251170 have been obtained in the determination of fourth roots of 30. The maximumerror 0.000002324581 and maximum percentage error 0.000232458100 have been obtained inthe determination of fourth roots of 1. The average value of the error is 0.000000392037 and theaverage value of percentage error is 0.000027500512. Minimum, maximum and average valuesof the numerical rate of convergence have been found to be 0.239808153477, 1.851851851852and 1.197514787730 respectively.

In this paper we test for convergence in access to clean energy and clean technology among nations in order to study the economic determinants of access to clean energy and clean technologies. This is important because without access to clean fuels, no global development strategy can be environmentally sustainable. After obtaining an estimated convergence rate under a conditional β -convergence model, we use a more sophisticated club convergence econometric framework and ultimately reject the hypothesis of β -convergence in favor of subgroups exhibiting intra-group convergence tendencies that are distinct from the other groups. We then employ a club convergence algorithm which groups the 93 nations studied into 8 convergence clubs based on characteristics including the percentage of the population with access to clean energy in the household and the growth rate of this percentage. Evidence that household access to clean energy and clean technology is tied to economic development and institutional quality is provided by showing that the convergence clubs not only reflect distinct strata in access to clean energy but are also strongly tied to important indicators of institutional quality.

This paper aims to explain the growth experiences of 14 major states of India between 1980 and 1998. Using two measures of convergence, σ-convergence and ß-convergence, we examine whether per capita incomes in the states have been converging or diverging. By both standards of convergence, India demonstrated overall divergence during 1980–;98, as well as during both the pre-reform and post-reform subperiods. Interestingly, the richer states experienced a degree of convergence during the post-reform period, whereas the poorer states did not. Divergence was most notable within the poorer group of states. A remarkable 82 percent of the cross-state variation in growth is explained by just the urbanization variable in India, with no hint of any conditional convergence after controlling for the degree of urbanization. The regression estimate shows that a 10 percentage point higher rate of urbanization is associated with 1.3 percentage points per year higher rate of annual growth.

This paper examines the pattern of convergence in labour productivity across regions due to their ability to adopt technology. Whether regions exhibit a pattern of convergence depends on the degree to which infrastructure conditions are appropriate for the adoption of technological improvements. The ability of a region to adopt or create technology is reflected in the percentage of its labour force employed in technologically dynamic sectors or, more generally, in the resources devoted to science and technology. A high percentage of labour employed in technologically advanced sectors leads a region to a pattern of convergence. This hypothesis is tested using data for the NUTS-2 regions of the EU-27 during the time period 1995-2006. The results suggest that adoption of technology has a significant and positive effect on regional convergence in Europe. The analysis is also shown to have important implications for the direction of regional policy in Europe. To be more specific, regional policies, in order to enhance regional growth and convergence, should encourage employment in advanced technological sectors.

Abstract We propose using a simple Taylor rule to evaluate business cycle convergence of the Czech Republic, Hungary, and Poland with the Eurozone. Our findings indicate an ongoing convergence of those CEE countries to the Eurozone, but with instabilities and heterogeneity between the countries. Especially Poland has shown a high degree of convergence in recent years. But there are still relevant differences in Taylor rates of each country to the Eurozone of about two percentage points.

AbstractIncreasing the success rate of a process, i.e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal. At runtime, there are often certain actions (a.k.a. treatments) that workers may execute to lift the probability that a case ends in a positive outcome. For example, in a loan origination process, a possible treatment is to issue multiple loan offers to increase the probability that the customer takes a loan. Each treatment has a cost. Thus, when defining policies for prescribing treatments to cases, managers need to consider the net gain of the treatments. Also, the effect of a treatment varies over time: treating a case earlier may be more effective than later in a case. This paper presents a prescriptive monitoring method that automates this decision-making task. The method combines causal inference and reinforcement learning to learn treatment policies that maximize the net gain. The method leverages a conformal prediction technique to speed up the convergence of the reinforcement learning mechanism by separating cases that are likely to end up in a positive or negative outcome, from uncertain cases. An evaluation on two real-life datasets shows that the proposed method outperforms a state-of-the-art baseline.

Ageing of population and the percentage of disabled people are constantly growing, as well as the digital gap between them and the information society. In this paper we propose a new e-service provisioning model adopting TV as the most familiar channel to reach these audiences and to favor digital inclusion (e-inclusion) and social inclusion. The convergence of different DTT, IPTV and IPHN technologies allows to adopt new interfaces and input/output devices for an easier and more familiar interaction with this enhanced platform.

The concept of rural tourism has become one of the vital issues of economic and social benefits to society. This present study identifies different motivational factors that may directly or indirectly influence the tourists’ motivation. The primary objectives of this study include the growth, development, and emergence of rural tourism potentials at Kamarpukur as well as to analyze the tourists’ flow pattern and also examine the existing and future requirements in the motivational point of view. For fulfillment of the basic objective, data for the study were collected through field survey. The sample size was restricted to 200 respondents. Information gathered about tourists’ motivational factors include culture, tourism amenities, destination, and religion. The collected data have been analyzed using different statistical methods like percentage and Chi-square. The major findings of this study show, in the present scenario of above factors, how to attract more tourists for repeat visits and promote infrastructural requirement for better tourism service to increase the level of tourists’ motivation as well. In the policy implication point of view, this study is relevant for balancing the demand and supply of tourism motivational requirement indicators, which can offer better service excellence in the study area.

The stress concentration factor of different structural elements has been obtained analytical, experimental, and numerically. For the analytical part, there are several formulas established according to the element and the load condition to which the component is subjected. In the case of the numerical simulation results, they are approximations that depend on the refinement of the mesh. In this work, a comparative analysis was carried out between the analytical results and those obtained numerically from the stress concentration factor of a flat stepped bar subjected to tension, considering convergence criteria of 5%, 2% and 1%. An automatic mesh refinement tool was used, and several studies were run using design points. It was found that the average percentage variation between the analytical and the numerical approach according to the convergence criterion was 2.5%, 0.9% and 0.6%, respectively. Also, some points were found where the variation was notable.

Facial expression is the external expression of inner emotion, and is the main medium for analyzing emotion-guided sentiment, which has great research value. And for the problems of low accuracy and slow convergence of current models for face expression recognition. This paper proposed the ReSE face expression recognition model based on the residual network through the study of face expression recognition. The ReSE model is mainly constructed by ResNet18 and RE module, while using PReLU function instead of ReLU function, introducing Dropout function, and finally using island loss classification function. Through experimental validation, the average accuracy of the ReSE model for face expression recognition on the Fer2013 dataset is 1.33 percentage points higher than that of the VGG16 model; the average accuracy of the ReSE model for face expression recognition on the CK+ dataset is 1.36 percentage points higher than that of the ResNet18 model. Follow-up research needs to reduce the number of model parameters and further optimize the network structure for improving the accuracy of facial expression recognition.

The part of outcome inequality, which can be attributed to the unequal circumstances is considered as unfair and it is designated as inequality of opportunity in the outcome space. In this study we reckon this inequality of opportunity in the distribution of weekly wage and education in India by invoking two alternative methods of reckoning inequality of opportunity. Furthermore, it is evaluated from the results of estimations that inequality of opportunity in the distribution of labour market outcome can be attributed to the poor circumstances to achieve education, as the groups with poor circumstances in education as identified by the parametric model are the groups having greater percentage of opportunity inequality in the distribution of weekly wage. This finding corroborates the existence of a vicious cycle from low educational achievement to low earning to low educational achievement in India.

Faster data speeds, shorter end-to-end latencies, improved end-user service efficiency, and a wider range of multi-media applications are expected with the new 5G wireless services. The dramatic increase in the number of base stations required to meet these criteria, which undermines the low-cost constraints imposed by operators, demonstrates the need for a paradigm shift in modern network architecture. Alternative formats will be required for next-generation architectures, where simplicity is the primary goal. The number of connections is expected to increase rapidly, breaking the inherent complexity of traditional coherent solutions and lowering the resulting cost percentage. A novel implementation model is used to migrate complex-nature modulation structures in a highly efficient and cost-effective manner. Theoretical work to analyses modulations’ behavior over a wired/fiber setup and wireless mode is also provided. The state-of-the-art computational complexity, simplicity, and ease of execution while maintaining efficiency throughput and bit error rate.

The new energy wind power prediction model in the smart grid environment is studied, and a model based on the attention mechanism of time convolution network and two-way gated loop unit is proposed. The model utilizes time convolution network to mine the association between multidimensional time series data, introduces the residual module to accelerate the convergence speed, and combines the two-way gated recurrent unit and the attention mechanism to construct the time-sequence attention module, in order to improve the accuracy of wind power prediction. The experimental results show that the model performs well in terms of mean absolute value error, mean absolute value percentage error and coefficient of determination, which verifies its efficiency and accuracy in short-term wind power prediction.

This study presents an innovative method for predicting coal water supply pipeline leakage aperture sizes. Firstly, an Improved Grey Wolf Optimization (IGWO) algorithm is introduced, which combines Bernoulli chaotic initialization, elliptical convergence parameters, and dynamic weight updates. The algorithm’s optimization capabilities are enhanced by IGWO. Secondly, the effectiveness of IGWO is validated through benchmark tests. Finally, IGWO is applied to optimize the initial structural parameters of a Backpropagation (BP) neural network. The effectiveness of IGWO-BP is verified using laboratory pipeline infrasound leakage signals. The optimized IGWO-BP model demonstrates superior performance in predicting leakage apertures, with a substantial 69.12% reduction in mean absolute percentage error (MAPE) and a 66.96% decrease in mean square error (MSE) compared to traditional BP models, offering valuable insights for future leak remediation efforts.

Abstract This chapter summarizes the study’s findings and makes suggestions for the continued vitality of Spanish in Chicago and in the United States. It starts with a discussion of how to measure Spanish and support its vitality. The chapter then provides a summary of the study’s findings. It discusses conclusions about generation and proficiency, differences in regional groups, evidence of dialect leveling, and evidence of convergence for the five linguistic features analyzed: lexical familiarity, proportional use of so versus entonces, number of codeswitches and percentage of English use, production of subjunctive morphology in obligatory and variable contexts, and two phonological features, the weakening of coda /s/ and the velarization of /r̄/. For MexiRicans, it additionally discusses evidence of a “mother factor. The chapter closes with suggestions for areas of further research.

Abstract The University of Leeds has developed a high-fidelity mechanistic CO2 corrosion prediction model that simulates the underlying bulk equilibrium, mass transport, and electrochemical processes using a multiphysics simulation software. However, several characteristics of this model hinder its industry adoption, including licensing costs, the requirement for trained users, and the complexity of achieving satisfactory convergence when performing extended run-time large scale parametric sweeps. In this work we investigate the use of Machine Learning based surrogate modelling to combat these limitations, with the aim of developing a model to emulate the predictions of the existing Leeds multiphysics model which is more suitable for industry utilization. Six Machine Learning models were trained on over 160,000 CO2 corrosion rate predictions made by the Leeds multiphysics model, each with hyperparameters optimized accordingly. Preliminary analysis indicates predictions by the Deep Neural Network (DNN) and Extra Trees Regressor (ETR) models are most accurate, exhibiting the lowest root mean square error and mean absolute percentage error respectively. Further trade-offs between these models are discussed, highlighting significant improvements in simulation time, computational cost, and usability compared to the original model. Additionally, the DNN proves effective in detecting convergence issues and anomalies in Leeds multiphysics model output data.

This paper examines the matter of gender digital divide, a phenomenon which limits the equitable realization of digital transformation benefits. A synthesis of deep root causes is presented to better understand the issue and the factors contributing to women’s exclusion from digitalization. The case study examines the gender gap in the European Union by analyzing three indicators: percentage of the population who has used the internet in the past 12 months, percentage of the population who has used the internet to interact with public authorities, and percentage of population who has used the internet for online banking and e-commerce. Based on the indicators, gender gap was calculated in absolute and relative terms and the beta convergence is also analyzed. Results show the remarkable evolution in terms of both digital transformation and reducing the gender gap at EU-27 level and a distinct pattern of β-convergence, proving that countries which start with lower ICT indicators achieve higher growth over time. Most of the EU member states focused on the issue and created gender-adaptive policies which helped them reduce the gap in the past ten years. Finally, the paper displays a collection of such best practices and measures that promote complete participation and inclusion of women and girls in the digital revolution.

A systematic analysis of a single-rotor horizontal axis wind turbine aerodynamics is performed to obtain a realistic potential maximum efficiency. It is noted that by including the effects of swirl, viscosity and finite number of blades, the maximum aerodynamic efficiency of a HAWT is within a few percentage points of the efficiency of commercially-available turbines. The need for investigating windfarm (as a unit) aerodynamics is thus highlighted. An actuator disk model is developed and implemented in the OpenFOAM software suite. The model is validated against 1-D momentum theory, blade element momentum theory, as well as against experimental data. The validated actuator disk model is then used to investigate an interesting microscale meteorological phenomenon called “flow convergence” caused by an array of wind turbines. This phenomenon is believed to be caused by the drop of pressure in wind farms. Wind farm numerical simulations are conducted with various approximations to investigate and explain the flow convergence phenomenon.

A second order damage detection method is developed by expanding the original eigenparameters using their sensitivity terms with the variations in the structural variants. This vibration-based polynomial method is generated from eigenvalue re-analysis in conjunction with the polynomial algorithm. By incorporating basic forms of the Lagrange factor functions, numerical eigenparameter functions are generalized to multi-variate polynomial interpolated forms. Second order sensitivity terms are computed by differentiating these multi-variate eigenparameter functions with respect to the structural variants. Convergence of different order algorithms are compared using finite element model of a four element cantilever beam structure under various damaged percentage cases. Moreover, finite element model of a four bay modular space truss is established. Damage detections from small to large percentages are carried out through numerical simulations on the space truss. Most of these cases converge efficiently toward the ultimate solutions within 1% termination level. Therefore the BFGS algorithm works well with the nonlinear multi-variate system equations. The algorithm operates robustly with limited number of d.o.f.s in the reduced order model and limited number of vibration modes in the full model.

Abstract Multi-objective optimization is integral to control systems, particularly in engineering, where multiple objectives must be concurrently satisfied. This study pioneers a comprehensive comparison of 77 evolutionary algorithms for optimizing a second-order system under a proportional-integral-derivative (PID) controller. We emphasize the challenges of balancing conflicting metrics like peak time and percentage overshoot and how PID controller tuning is crucial in achieving this balance. To assess the algorithms’ performance, we utilize four different performance metrics, which encompass Generational Distance (GD), Spacing, Spread, and computation time. The optimization results are analyzed using two methods. Firstly, after 1 million iterations, outcomes are visually represented through discrete charts for each algorithm, detailing their performance metrics. The Multiple single objective Pareto sampling II (MSOPSII) algorithm demonstrates the most effective distribution of the solution set and maintains uniformity well. The Indicator-Based Evolutionary Algorithm (IBEA) excels in the Spacing Metric, while the Speed-constrained Multi-objective Particle Swarm Optimization (SMPSO) algorithm exhibits superior convergence. Secondly, algorithms with optimal performance are evaluated by considering multiple metrics simultaneously. The theta-Dominance-based Evolutionary Algorithm (tDEA) leads in combined convergence and spread, Multi-Tasking Constrained Multi-objective Optimization (MTCMO) stands out for convergence and spacing, and MSOPSII and IBEA perform best in spread and spacing. Across all three metrics, MOEA/D with Adaptive Weight Adjustment (MOEADAWA) emerges as the top performer. These outcomes not only advance our understanding of algorithmic efficiency in multi-objective scenarios but also provide valuable insights for the application of these algorithms in practical control system challenges. This research fills a critical gap in existing literature, offering an in-depth evaluation of a wide range of algorithms in the context of control systems.

Abstract Thermal barrier coatings (TBCs) applied to combustion chamber surfaces aim to increase engine efficiency by reducing heat transfer via elevated surface temperatures during combustion. This work presents a computational study of TBCs in the partially premixed compression ignition-diffusion concept of gasoline compression ignition (GCI) using a computational fluid dynamics (CFD)-finite element analysis (FEA) co-simulation. The in-cylinder processes are simulated in CFD and the predicted heat flux is passed to FEA to resolve the spatially and temporally varying surface temperature profile of the TBC-coated engine parts. This surface temperature profile is subsequently passed back to CFD in an iterative process until convergence is achieved. The results indicate that performing a CFD-FEA co-simulation is critical to accurately predict the heat transfer, and by extension the efficiency, of an engine cycle operating in a mixing controlled mode of combustion compared to using an assumed constant piston temperature. Even an uncoated metal piston displays significant spatial variation of the piston surface temperature as well as the heat flux. The results also indicate that the 250 micron Gadolinium Zirconate Oxide (GZO) coating experienced an average temperature swing of > 100 K at 10 bar IMEPn, while high heat flux areas under the plume experienced a local temperature swing of up to 300 K. This led to an efficiency improvement of ∼0.4 percentage points, agreeing with experiments. When the simulation was performed at 15 bar IMEPn, a substantial efficiency benefit of 1.4 percentage points was observed, while the experimental results indicated a slight indicated efficiency penalty. The only apparent explanation of this discrepancy is the occurrence of a convection vive effect, which is not captured by the CFD simulation. Small combustion chamber height in a light-duty engine exacerbates the effect, due to the close proximity of the burning jet to the piston and head surfaces throughout combustion.

Abstract Past studies have tried to understand the impact of the tire to understand its contribution to the overall drag on the vehicle. However, some features of the tire have not been studied to the extent to which is necessary to improve the drag performance of the tire. One such feature of the tire is the rim protector. The rim protector can have a considerable impact on the total drag contribution of the tire. In this study, the tire rim protector is parametrized, and design of experiments technique is used to understand the influence of the parameters on the drag performance of the tire as well as the effect on the flow structures around the tire. In this study, a standalone tire model is used. The rim protector cross-section profile is simplified to a triangle. Both the base angles of the triangle as well as the altitude of this triangle are used as input parameters of the rim protector. Upon deciding the range of these parameters, the Kennard-Stone algorithm is used to create parameter sets to simulate for. Simulations were conducted in the open road domain. The open road domain was recreated using a cuboid enclosure with a vastly large volume with respect to the tire. Mesh parameters are chosen based on a grid convergence study. A turbulent flow regime and a transient time regime are used. The SST K-Omega turbulence model is selected for the simulation. Rotating wheel and moving ground boundary conditions are used. Drag area, which is influenced by the coefficient of drag and the frontal area of the tire, is chosen as the metric for the sensitivity study. A local sensitivity percentage is calculated, and 3D response surfaces are plotted to understand the impact of each of the parameters based on the drag area results from the design space. It was found that of the three parameters, the altitude effected the drag performance of the tire the most, with a local sensitivity percentage of 70%. On the other hand, the base angles of the rim protector geometry each had a local sensitivity percentage of 20% and 10% each. This gives a very clear idea of how the rim protector shape can affect the drag performance of a tire. For further studies, a more detailed analysis on drag optimization can be conducted for the rim protector cross sectional geometry.

Minimizing entropy generation is important to improve the efficiency of any system. The objective of this study is to use computational fluid dynamics (CFD) to elucidate the effects of pressure gradients on entropy generation rates in laminar and transitional boundary layers. The commercial CFD software, ANSYS FLUENT, is employed. The favorable and adverse pressure gradients are generated using various curved slip top walls. Bypass transition is simulated using the mean inlet velocity and Reynolds stresses from the direct numerical simulation (DNS) conducted by Nolan and Zaki [1]. Various turbulence and transitional models are employed and the results are compared to the DNS data. The factor of safety method is used to evaluate numerical error and grid uncertainties. Three systematically refined meshes are used to evaluate grid convergence. Monotonic convergence is achieved for all simulations with small grid uncertainties. The boundary layer correlation function, F(λ), the shear stress correlation, S(λ), and the dissipation coefficient, Cd, are calculated for the laminar CFD results. The dissipation coefficient, Cd and the intermittency, γ, are also calculated for the bypass transition CFD results. The laminar CFD results show better agreement with the correlation developed by McEligot than with the Thwaites correlation for F(λ) and S(λ). Overall, the percentage differences between the CFD results and the correlations increase as the magnitude of the pressure gradient variable, β, increases. The solvers and turbulence models in the transitional simulations are similar to the study by Ghasemi et al [2]. However, this study uses a much finer grid and improved boundary conditions for the inlet. These changes show an improvement for most turbulence models by comparison with the DNS results, especially for the location of transition.

Recent years, Genetic Algorithm (GA) technique has been gotten much more attention in solving real-world problems, more successful genetic algorithms applications to engineering optimization have shown the technique has strong ability of global searching and optimizing based on various objectives for their optimal parameters. The technique may be applied to more complicated heat exchangers and is particularly useful for new types. It is important to optimize heat exchanger, for minimum volume/weight to save fabrication cost or for improved effectiveness to save energy consumption, under requirement of allowable pressure drop; simultaneously it is mandatory to optimize geometry parameters of heat plate from the technical and economic standpoints. In this paper, GA is used to optimize the Cross Wavy Primary Surface (CWPS) and Cross Corrugated Primary Surface (CCPS) geometry characteristic of recuperator in 100kW microturbine, in order to get more compactness and minimum volume and weight. Two kinds of fitness assignment methods were considered. Furthermore, the GA parameters were set optimally to yield smoother and faster fitness convergence. The comparison shows the superiority of GA and confirms its potential to solve the objective problem. When the rectangular recuperator core size and corrugated geometries are evaluated, in the CWPS the weight of recuperator decreases 12% or more, the coefficient of compactness increases by up to 19%, with an increase of total pressure drop by a percentage of 0.84 compared to the original design data, the total pressure drop as a percentage of the operating pressure is controlled to be less than 3%. In the CCPS area compactness is increased to 70% the initial design result by decreasing pitch and relatively high height of the passage, the weight decreases by 17% to 36%, depending on different inclination angle (θ). Comparatively the CCPS shows superior performance for use in compact recuperators of the future. The GA technique chooses from a variety of geometry characters, optimizes them and picks out the one which provides the closest fit to the recupertor for microturbine.

The purpose of this document is to describe a version of the Global Trade Analysis Project (GTAP) computable general equilibrium (CGE) model implemented in the General Algebraic Modeling System (GAMS) that is a literal implementation of the standard General Economic Modeling Package (GEMPACK) version. It updates and supersedes the model description provided in van der Mensbrugghe (2018), which remains the main reference. The key revision of the new version is that the model is calibrated to initially normalized variables, similar to Rutherford’s GTAPinGams model (Lanz and Rutherford (2016)). One objective is to improve model scaling and hopefully numerical convergence. One advantage is that it is relatively easy to view the results in percentage change form, similar to the GEMPACK version of the model. The new version includes three additional extensions: national-level Armington preferences for domestic vs. imports, agent-level sourcing by region of origin (a variant of the multi-region input-output model (MRIO)), and rent-generating ad valorem equivalent (AVE) of non-tariff measures (NTMs).

There is scant empirical economic research regarding the way that Latin American governments efficiently allocate their spending across different functions to achieve higher growth. While most papers restrict their analysis to the size of government, much less is known about the composition of spending and its implications for long-term growth. This paper sheds light on how allocating expenditures to investment in quality human and physical capital, and avoiding waste on inefficient expenditures, enhance growth in Latin America. This paper uses a novel dataset on physical and human capital and detailed public spending that includes -for the first time- Latin American countries, which is categorized by a cross-classification that provides the breakdown of government expenditure, both, by economic and by functional heads. The database covers 42 countries of the OECD and LAC between 1985 and 2017. There are five main results. First, the estimated growth equations show significant positive effects of the factors of production on growth and plausible convergence rates (about 2 percent). The estimated effect of the physical investment rate is positive and significant with a long-run elasticity of 1.2. Second, while the addition of years of education as a proxy for human capital tends to have no effect on growth, the addition of a new variable that measures quality-adjusted years of schooling as a proxy for human capital turns out to have a positive and significant effect across all specifications with a long-run elasticity of 1.1. However, if public spending on education (excluding infrastructure spending) is added to the factor specification, growth is not affected. This is mainly because, once quality is considered, spending more on teacher salaries has no effect on student outcomes. Therefore, the key is to increase quality, not just school performance or education spending. Third, both physical and human capital are equally important for growth: the effect of increasing one standard deviation of physical capital or human capital statistically has the same impact on economic growth. Fourth, increasing public investment spending (holding public spending constant) is positive and significant for growth (a 1% increase in public investment would increase the long-term GDP per capita by about 0.3 percent), in addition to the effect of the private investment rate. However, the effect of public spending on payroll, pensions and subsidies does not contribute to economic growth. Fifth, the overall effect of the size of public spending on economic growth is negative in most specifications. An increase in the size of government by about 1 percentage point would decrease 4.1 percent the long-run GDP per capita, but the more effective the government is, the less harmful the size of government is for long-term growth.

In 2024, the macroeconomic adjustment process continued, characterized by a sustained reduction in inflation that began in 2023 and a decline in the current account deficit of the balance of payments. This adjustment took place in the context of a contractionary monetary policy, with a gradual reduction in the monetary policy interest rate. GDP grew by 1.7%, driven by investment and consumption, while employment increased by 2.2%. Foreign reserves remained at adequate levels, and Banco de la República recorded a profit of COP 10,041 billion, benefiting from the returns on foreign reserves. Macroeconomic environment The International Monetary Fund (IMF) and the World Bank estimate that the global economy grew by 3.2% in 2024, a rate similar to that observed in 2023 (3.3%). This occurred in a context of moderating inflation and declining monetary policy interest rates in most countries. Global inflation moderated over the course of 2024. However, inflation rebounded toward the end of the year in some advanced economies, mainly due to rising energy costs. In Latin America, inflation trends were mixed. While some economies experienced sustained price stability, in most cases, inflation remained above the targets set by their respective central banks. Monetary policy interest rates in most Latin American economies continued to decline, reflecting a moderation in inflation and inflation expectations. However, some countries in the region recently raised interest rates in response to renewed inflationary pressures. Oil production increased in 2024, leading to a 3% decrease in oil prices, with Brent crude averaging around USD 80 per barrel. However, geopolitical tensions prevented a more pronounced decline. The U.S. dollar appreciated against most currencies, driven by expectations that the Federal Reserve (Fed) would implement more gradual policy rate cuts. In 2025, global economic growth is projected to be similar to that of 2024, supported by declining inflation, wage recovery, sustained employment growth, and a less restrictive monetary policy stance. However, geopolitical tensions and U.S. trade policies introduce uncertainty. More gradual reductions in the Fed’s interest rate are expected, with the possibility of pauses if inflationary pressures resurface. In Latin America, central banks are expected to continue cutting interest rates, although monetary policy may remain contractionary where inflation has not yet reached target levels. Domestic economic activity Colombia’s GDP grew by 1.7% in 2024, reflecting a moderate recovery compared to the previous year. This occurred in an environment of lower interest rates, improved domestic demand, and an increase in remittances and exports. Private consumption and fixed capital investment—particularly in infrastructure projects such as the Bogotá metro—contributed to economic growth. However, investment in housing declined. Agricultural and services sectors led economic growth, while mining and manufacturing contracted. The loan portfolio experienced low nominal growth, though some segments showed signs of recovery toward the end of the year. For 2025, economic activity is expected to continue recovering, approaching its productive capacity and aligning with the convergence of inflation toward its target. Employment Employment grew by 2.2% in 2024, resulting in the creation of 508,000 jobs. This expansion was driven by rural areas, where employment increased by 3.2%, surpassing the 1.4% growth in urban areas. The commerce, accommodation, manufacturing, public administration, health, and education sectors were the primary contributors to job creation. Wage employment grew by 2.7%, exceeding pre-pandemic levels, while non-wage employment increased by 1.8%, leading to a decline in informality to 55.6%. The national unemployment rate fell by 0.6 percentage points, reaching 9.7%, with a more pronounced reduction in rural areas. For 2025, the unemployment rate is expected to remain stable, supported by a positive economic outlook. Inflation and Monetary Policy Headline inflation in Colombia fell significantly from 9.3% in 2023 to 5.2% in 2024, primarily due to a restrictive monetary policy that moderated domestic demand and contributed to a reduction in the current account deficit. Core inflation (excluding food and regulated products) declined from 8.4% to 5.2%, reflecting the effectiveness of contractionary monetary policy. Inflation of goods dropped sharply, from 7.1% to 0.6%, due in part to the resolution of logistical disruptions and the appreciation of the peso. In contrast, services inflation declined more moderately, from 9% to 7%, influenced by indexation to past inflation and the increase in the minimum wage. Prices of food decreased from 5.0% to 3.3%, driven by lower pressures on processed food prices, benefiting from reduced costs of imported raw materials and a favorable exchange rate. Prices of regulated items dropped to 7.3%, following smaller adjustments in gasoline prices (after the required increases in 2023) and lower electricity and public service tariff increases, except for gas prices, which continued to rise. Inflation is expected to continue converging toward the 3% target in 2025, with headline inflation projected to close the year at around 4.1%, continuing its downward path into 2026. However, new risks have emerged, including a recent rise in producer costs, a significant increase in the minimum wage, and a rebound in inflation expectations. Balance of payments Colombia’s current account deficit narrowed to 1.7% of GDP between January and September 2024, down from 2.5% in the same period in 2023. This improvement was driven by higher remittance inflows, an improved services trade balance, and lower factor income outflows. Remittances reached a record USD 11,848 million, with the United States and Spain as the main sources of these inflows. A decline in the profits of foreign direct investment (FDI) companies, particularly in the oil and coal sectors, also contributed to reducing external imbalances. The trade deficit widened due to a greater imbalance in the trade of goods within a context of lower commodity prices. However, this was partially offset by strong agricultural and industrial exports. Additionally, the good performance of service exports, supported by higher international tourist arrivals, helped contain a larger trade imbalance. The financial account recorded net capital inflows equivalent to 1.1% of GDP, lower than the 2.5% recorded in 2023, primarily due to a decline in foreign direct investment in mining, transportation, and oil. This was partially offset by growth in financial and business services investment. The current account deficit is estimated to have closed 2024 at 1.8% of GDP, with a projected widening to 2.5% in 2025, in line with higher expected economic growth and stronger domestic demand. Public finances According to preliminary figures from the 2025 Financial Plan (PF-25) presented by the Ministry of Finance and Public Credit (MHCP), Colombia’s General Government deficit reached 4.8% of GDP in 2024, marking a 2.1 percentage-point increase compared to 2023. This deterioration was mainly driven by a worsening in the balances of the Central National Government (GNC) (2.6 pp) and the Social Security subsector (0.4 pp), partially offset by a 0.8 pp improvement in Regional and Local Government balances. The reduction in the deficit position of the Fuel Price Stabilization Fund (FEPC for its acronym in Spanish) was notable, following gasoline price adjustments, which closed the gap between the reference price and local market prices. However, fiscal pressures persist due to ongoing subsidies for ACPM (diesel fuel). The total and primary deficits of the Central Government stood at 6.8% and 2.4% of GDP, respectively, driven by a decline in tax revenue—particularly from income and external taxes—alongside increased government spending. The net debt of the Central Government increased to 60% of GDP, exceeding previous forecasts. For 2025, a total and primary deficit of 5.1% and 0.2% of GDP is projected, with tax revenue expected to grow by 22.6%. Compliance with the fiscal rule and the stabilization of public finances will be critical in 2025, given the potential impact of fiscal slippage on the country’s risk premiums. Failure to meet fiscal targets could raise interest rates for both the Government and the broader economy. Maintaining credibility in fiscal policy will be key to preventing macroeconomic adjustments from exerting additional pressure on interest rates. International Reserves As of December 31, 2024, Colombia’s net international reserves stood at USD 62,481 million, reflecting an increase of USD 2,873 million during the year. This growth was primarily driven by returns on reserves, which reached 3.65%, benefiting from higher global interest rates, and Banco de la República's reserve accumulation program, which added USD 1,479.4 million to reserves. According to the IMF’s reserve adequacy methodology, Colombia maintains a reserve ratio of 1.29. This falls within the adequate range (1.0 – 1.5), indicating that Colombia’s reserves are sufficient to withstand extreme external shocks and balance of payments risks. Profits obtained by Banco de la República The Bank's profits reached a record COP 10,041 billion in 2024, resulting from revenues of COP 13,948 billion and expenses of COP 3,907 billion. Profits increased by COP 815 billion compared to 2023, primarily due to lower expenses, although partially offset by a decline in revenues. For 2025, profits are projected at COP 10,512 billion, supported by the high expected profitability of foreign reserves. However, this projection is subject to uncertainty related to reserve performance and monetary base growth.

Banco de la República is celebrating its 100th anniversary in 2023. This is a very significant anniversary and one that provides an opportunity to highlight the contribution the Bank has made to the country’s development. Its track record as guarantor of monetary stability has established it as the one independent state institution that generates the greatest confidence among Colombians due to its transparency, management capabilities, and effective compliance with the central banking and cultural responsibilities entrusted to it by the Constitution and the Law. On a date as important as this, the Board of Directors of Banco de la República (BDBR) pays tribute to the generations of governors and officers whose commitment and dedication have contributed to the growth of this institution.1 Banco de la República’s mandate was confirmed in the National Constitutional Assembly of 1991 where the citizens had the opportunity to elect the seventy people who would have the task of drafting a new constitution. The leaders of the three political movements with the most votes were elected as chairs to the Assembly, and this tripartite presidency reflected the plurality and the need for consensus among the different political groups to move the reform forward. Among the issues considered, the National Constitutional Assembly gave special importance to monetary stability. That is why they decided to include central banking and to provide Banco de la República with the necessary autonomy to use the instruments for which they are responsible without interference from other authorities. The constituent members understood that ensuring price stability is a state duty and that the entity responsible for this task must be enshrined in the Constitution and have the technical capability and institutional autonomy necessary to adopt the decisions they deem appropriate to achieve this fundamental objective in coordination with the general economic policy. In particular, Article 373 established that “the State, through Banco de la República, shall ensure the maintenance of the purchasing power of the currency,” a provision that coincided with the central banking system adopted by countries that have been successful in controlling inflation. In 1999, in Ruling 481, the Constitutional Court stated that “the duty to maintain the purchasing power of the currency applies to not only the monetary, credit, and exchange authority, i.e., the Board of Banco de la República, but also those who have responsibilities in the formulation and implementation of the general economic policy of the country” and that “the basic constitutional purpose of Banco de la República is the protection of a sound currency. However, this authority must take the other economic objectives of state intervention such as full employment into consideration in their decisions since these functions must be coordinated with the general economic policy.” The reforms to Banco de la República agreed upon in the Constitutional Assembly of 1991 and in Act 31/1992 can be summarized in the following aspects: i) the Bank was assigned a specific mandate: to maintain the purchasing power of the currency in coordination with the general economic policy; ii) the BDBR was designatedas the monetary, foreign exchange, and credit authority; iii) the Bank and its Board of Directors were granted a significant degree of independence from the government; iv) the Bank was prohibited from granting credit to the private sector except in the case of the financial sector; v) established that in order to grant credit to the government, the unanimous vote of its Board of Directors was required except in the case of open market transactions; vi) determined that the legislature may, in no case, order credit quotas in favor of the State or individuals; vii) Congress was appointed, on behalf of society, as the main addressee of the Bank’s reporting exercise; and viii) the responsibility for inspection, surveillance, and control over Banco de la República was delegated to the President of the Republic. The members of the National Constitutional Assembly clearly understood that the benefits of low and stable inflation extend to the whole of society and contribute mto the smooth functioning of the economic system. Among the most important of these is that low inflation promotes the efficient use of productive resources by allowing relative prices to better guide the allocation of resources since this promotes economic growth and increases the welfare of the population. Likewise, low inflation reduces uncertainty about the expected return on investment and future asset prices. This increases the confidence of economic agents, facilitates long-term financing, and stimulates investment. Since the low-income population is unable to protect itself from inflation by diversifying its assets, and a high proportion of its income is concentrated in the purchase of food and other basic goods that are generally the most affected by inflationary shocks, low inflation avoids arbitrary redistribution of income and wealth.2 Moreover, low inflation facilitates wage negotiations, creates a good labor climate, and reduces the volatility of employment levels. Finally, low inflation helps to make the tax system more transparent and equitable by avoiding the distortions that inflation introduces into the value of assets and income that make up the tax base. From the monetary authority’s point of view, one of the most relevant benefits of low inflation is the credibility that economic agents acquire in inflation targeting, which turns it into an effective nominal anchor on price levels. Upon receiving its mandate, and using its autonomy, Banco de la República began to announce specific annual inflation targets as of 1992. Although the proposed inflation targets were not met precisely during this first stage, a downward trend in inflation was achieved that took it from 32.4% in 1990 to 16.7% in 1998. At that time, the exchange rate was kept within a band. This limited the effectiveness of monetary policy, which simultaneously sought to meet an inflation target and an exchange rate target. The Asian crisis spread to emerging economies and significantly affected the Colombian economy. The exchange rate came under strong pressure to depreciate as access to foreign financing was cut off under conditions of a high foreign imbalance. This, together with the lack of exchange rate flexibility, prevented a countercyclical monetary policy and led to a 4.2% contraction in GDP that year. In this context of economic slowdown, annual inflation fell to 9.2% at the end of 1999, thus falling below the 15% target set for that year. This episode fully revealed how costly it could be, in terms of economic activity, to have inflation and exchange rate targets simultaneously. Towards the end of 1999, Banco de la República announced the adoption of a new monetary policy regime called the Inflation Targeting Plan. This regime, known internationally as ‘Inflation Targeting,’ has been gaining increasing acceptance in developed countries, having been adopted in 1991 by New Zealand, Canada, and England, among others, and has achieved significant advances in the management of inflation without incurring costs in terms of economic activity. In Latin America, Brazil and Chile also adopted it in 1999. In the case of Colombia, the last remaining requirement to be fulfilled in order to adopt said policy was exchange rate flexibility. This was realized around September 1999, when the BDBR decided to abandon the exchange-rate bands to allow the exchange rate to be freely determined in the market.Consistent with the constitutional mandate, the fundamental objective of this new policy approach was “the achievement of an inflation target that contributes to maintaining output growth around its potential.”3 This potential capacity was understood as the GDP growth that the economy can obtain if it fully utilizes its productive resources. To meet this objective, monetary policy must of necessity play a countercyclical role in the economy. This is because when economic activity is below its potential and there are idle resources, the monetary authority can reduce the interest rate in the absence of inflationary pressure to stimulate the economy and, when output exceeds its potential capacity, raise it. This policy principle, which is immersed in the models for guiding the monetary policy stance, makes the following two objectives fully compatible in the medium term: meeting the inflation target and achieving a level of economic activity that is consistent with its productive capacity. To achieve this purpose, the inflation targeting system uses the money market interest rate (at which the central bank supplies primary liquidity to commercial banks) as the primary policy instrument. This replaced the quantity of money as an intermediate monetary policy target that Banco de la República, like several other central banks, had used for a long time. In the case of Colombia, the objective of the new monetary policy approach implied, in practical terms, that the recovery of the economy after the 1999 contraction should be achieved while complying with the decreasing inflation targets established by the BDBR. The accomplishment of this purpose was remarkable. In the first half of the first decade of the 2000s, economic activity recovered significantly and reached a growth rate of 6.8% in 2006. Meanwhile, inflation gradually declined in line with inflation targets. That was how the inflation rate went from 9.2% in 1999 to 4.5% in 2006, thus meeting the inflation target established for that year while GDP reached its potential level. After this balance was achieved in 2006, inflation rebounded to 5.7% in 2007, above the 4.0% target for that year due to the fact that the 7.5% GDP growth exceeded the potential capacity of the economy.4 After proving the effectiveness of the inflation targeting system in its first years of operation, this policy regime continued to consolidate as the BDBR and the technical staff gained experience in its management and state-of-the-art economic models were incorporated to diagnose the present and future state of the economy and to assess the persistence of inflation deviations and expectations with respect to the inflation target. Beginning in 2010, the BDBR established the long-term 3.0% annual inflation target, which remains in effect today. Lower inflation has contributed to making the macroeconomic environment more stable, and this has favored sustained economic growth, financial stability, capital market development, and the functioning of payment systems. As a result, reductions in the inflationary risk premia and lower TES and credit interest rates were achieved. At the same time, the duration of public domestic debt increased significantly going from 2.27 years in December 2002 to 5.86 years in December 2022, and financial deepening, measured as the level of the portfolio as a percentage of GDP, went from around 20% in the mid-1990s to values above 45% in recent years in a healthy context for credit institutions.Having been granted autonomy by the Constitution to fulfill the mandate of preserving the purchasing power of the currency, the tangible achievements made by Banco de la República in managing inflation together with the significant benefits derived from the process of bringing inflation to its long-term target, make the BDBR’s current challenge to return inflation to the 3.0% target even more demanding and pressing. As is well known, starting in 2021, and especially in 2022, inflation in Colombia once again became a serious economic problem with high welfare costs. The inflationary phenomenon has not been exclusive to Colombia and many other developed and emerging countries have seen their inflation rates move away from the targets proposed by their central banks.5 The reasons for this phenomenon have been analyzed in recent Reports to Congress, and this new edition delves deeper into the subject with updated information. The solid institutional and technical base that supports the inflation targeting approach under which the monetary policy strategy operates gives the BDBR the necessary elements to face this difficult challenge with confidence. In this regard, the BDBR reiterated its commitment to the 3.0% inflation target in its November 25 communiqué and expects it to be reached by the end of 2024.6 Monetary policy will continue to focus on meeting this objective while ensuring the sustainability of economic activity, as mandated by the Constitution. Analyst surveys done in March showed a significant increase (from 32.3% in January to 48.5% in March) in the percentage of responses placing inflation expectations two years or more ahead in a range between 3.0% and 4.0%. This is a clear indication of the recovery of credibility in the medium-term inflation target and is consistent with the BDBR’s announcement made in November 2022. The moderation of the upward trend in inflation seen in January, and especially in February, will help to reinforce this revision of inflation expectations and will help to meet the proposed targets. After reaching 5.6% at the end of 2021, inflation maintained an upward trend throughout 2022 due to inflationary pressures from both external sources, associated with the aftermath of the pandemic and the consequences of the war in Ukraine, and domestic sources, resulting from: strengthening of local demand; price indexation processes stimulated by the increase in inflation expectations; the impact on food production caused by the mid-2021 strike; and the pass-through of depreciation to prices. The 10% increase in the minimum wage in 2021 and the 16% increase in 2022, both of which exceeded the actual inflation and the increase in productivity, accentuated the indexation processes by establishing a high nominal adjustment benchmark. Thus, total inflation went to 13.1% by the end of 2022. The annual change in food prices, which went from 17.2% to 27.8% between those two years, was the most influential factor in the surge in the Consumer Price Index (CPI). Another segment that contributed significantly to price increases was regulated products, which saw the annual change go from 7.1% in December 2021 to 11.8% by the end of 2022. The measure of core inflation excluding food and regulated items, in turn, went from 2.5% to 9.5% between the end of 2021 and the end of 2022. The substantial increase in core inflation shows that inflationary pressure has spread to most of the items in the household basket, which is characteristic of inflationary processes with generalized price indexation as is the case in Colombia. Monetary policy began to react early to this inflationary pressure. Thus, starting with its September 2021 session, the BDBR began a progressive change in the monetary policy stance moving away from the historical low of a 1.75% policy rate that had intended to stimulate the recovery of the economy. This adjustment process continued without interruption throughout 2022 and into the beginning of 2023 when the monetary policy rate reached 12.75% last January, thus accumulating an increase of 11 percentage points (pp). The public and the markets have been surprised that inflation continued to rise despite significant interest rate increases. However, as the BDBR has explained in its various communiqués, monetary policy works with a lag. Just as in 2022 economic activity recovered to a level above the pre-pandemic level, driven, along with other factors, by the monetary stimulus granted during the pandemic period and subsequent months, so too the effects of the current restrictive monetary policy will gradually take effect. This will allow us to expect the inflation rate to converge to 3.0% by the end of 2024 as is the BDBR’s purpose.Inflation results for January and February of this year showed declining marginal increases (13 bp and 3 bp respectively) compared to the change seen in December (59 bp). This suggests that a turning point in the inflation trend is approaching. In other Latin American countries such as Chile, Brazil, Perú, and Mexico, inflation has peaked and has begun to decline slowly, albeit with some ups and downs. It is to be expected that a similar process will take place in Colombia in the coming months. The expected decline in inflation in 2023 will be due, along with other factors, to lower cost pressure from abroad as a result of the gradual normalization of supply chains, the overcoming of supply shocks caused by the weather, and road blockades in previous years. This will be reflected in lower adjustments in food prices, as has already been seen in the first two months of the year and, of course, the lagged effect of monetary policy. The process of inflation convergence to the target will be gradual and will extend beyond 2023. This process will be facilitated if devaluation pressure is reversed. To this end, it is essential to continue consolidating fiscal sustainability and avoid messages on different public policy fronts that generate uncertainty and distrust. 1 This Report to Congress includes Box 1, which summarizes the trajectory of Banco de la República over the past 100 years. In addition, under the Bank’s auspices, several books that delve into various aspects of the history of this institution have been published in recent years. See, for example: Historia del Banco de la República 1923-2015; Tres banqueros centrales; Junta Directiva del Banco de la República: grandes episodios en 30 años de historia; Banco de la República: 90 años de la banca central en Colombia. 2 This is why lower inflation has been reflected in a reduction of income inequality as measured by the Gini coefficient that went from 58.7 in 1998 to 51.3 in the year prior to the pandemic. 3 See Gómez Javier, Uribe José Darío, Vargas Hernando (2002). “The Implementation of Inflation Targeting in Colombia”. Borradores de Economía, No. 202, March, available at: https://repositorio.banrep.gov.co/handle/20.500.12134/5220 4 See López-Enciso Enrique A.; Vargas-Herrera Hernando and Rodríguez-Niño Norberto (2016). “The inflation targeting strategy in Colombia. An historical view.” Borradores de Economía, No. 952. https://repositorio.banrep.gov.co/handle/20.500.12134/6263 5 According to the IMF, the percentage change in consumer prices between 2021 and 2022 went from 3.1% to 7.3% for advanced economies, and from 5.9% to 9.9% for emerging market and developing economies. 6 https://www.banrep.gov.co/es/noticias/junta-directiva-banco-republica-reitera-meta-inflacion-3