Academic literature on the topic 'One-factor interest rate models'

One-factor no-arbitrage term structure models where the instantaneous interest rate follows either the process proposed by Vasicek (1977) or by Cox, Ingersoll, and Ross (1985), commonly known as CIR, are parsimonious and analytically tractable. Models based on the original CIR process have the important characteristic of allowing for a time-varying conditional interest rate volatility but are undefined in negative interest rate environments. A Shifted-CIR no-arbitrage term structure model, where the instantaneous interest rate is given by the sum of a constant lower bound and a non-negative CIR-like process, allows for negative yields and benefits from similar tractability of the original CIR model. Based on the U.S. and German yield curve data, the Vasicek and Shifted-CIR specifications, both considering constant and time-varying risk premia, are compared in terms of information criteria and forecasting ability. Information criteria prefer the Shifted-CIR specification to models based on the Vasicek process. It also provides similar or better in-sample and out-of-sample forecasting ability of future yield curve movements. Introducing a time variation of the interest rate risk premium in no-arbitrage one-factor term structure models is instead not recommended, as it provides worse information criteria and forecasting performance.

Multi-factor interest-rate models are widely used. Contingent claims with early exercise features are often valued by resorting to trees, finite-difference schemes and Monte Carlo simulations. When jumps are present, however, these methods are less effective. In this work we develop an algorithm based on a sequence of measure changes coupled with Fourier transform solutions of the pricing partial integro-differential equation to solve the pricing problem. The new algorithm, which we call the irFST method, also neatly computes option sensitivities. Furthermore, we are also able to obtain closed-form formulae for accrual swaps and accrual range notes. We demonstrate the versatility and precision of the method through numerical experiments on European, Bermudan and callable bond options, accrual swaps and accrual range notes.

The uncertainty attached to future movements of interest rates is an essential part of the Financial Decision Theory and requires an awareness of the stochastic movement of these rates. Several approaches have been proposed for modeling the one-factor short rate models where some lead to arbitrage-free term structures. However, no definite consensus has been reached with regard to the best approach for interest rate modeling. In this work, we briefly examine the existing one-factor interest rate models and calibrate Vasicek and Hull-White (Extended Vasicek) Models by using Turkey'
s term structure. Moreover, a trinomial interest rate tree is constructed to represent the evolution of Turkey&rsquo
s zero coupon rates.

Includes bibliographical references
This paper revisits pricing and hedging differences presented by Z. Guan, et. al., 2008 from a South African context. The Asset Liabilities Management (ALM) departments in large financial institutions are plagued by a number of problems. Among them is the choice of interest rate model for managing the risks associated with mortgage (home loan) repay-ments. This paper will address these problems by comparing various one-factor models, including Hull-White, Black-Karasinski and CIR models for the pricing and hedging of long-term Bermudan Swaptions which resembles mortgage loans in banks' books.

Includes bibliographical references (leaves 33-36).
This paper presents the results of Gaussian estimation of the South African short-term interest rate. It uses the same Gaussian estimation techniques employed by Nowman (1997) to estimate the South African short-term interest rate using South afrcan Treasury bill data. A range of single-factor continuous-time models of the short-term interest rate are estimated using a discrete-time model and compared to a discrete approximation used by Chan, Karolyi, Lonstaff and Sanders (1992a). We find that the process followed by the South African short-term interest rate is best explained by the Constant Elasticity of Variance (CEV) model and that the conditional volatility depends to some extent on the level of the interest rate. In addition we find evidence of a structural break in the mid-1980s, confirming our suspicions that the financial liberalisation of that period affected the short rate process.

In this thesis we study three different, but interconnected low-factor market models: LIBOR market model, Markov-functional model, and two-currency Markov-functional model. The LIBOR market model (LMM) is one of the most popular term structure models. However, it suffers from a major drawback, it is high-dimensional. The problem of highdimensionality can be in part solved imposing a separability condition. We will be interested how the separability condition interacts with time-homogeneity, a desirable property of an LMM. We address this question by parametrising two- and three-factor separable and time-homogeneous LMMs and show that they are of practical interest. Markov-functional models (MFMs) are a computationally efficient alternative to the LMMs. We consider two aspects of the MFMs, implementation and specification. First we provide two new algorithms that can be used to implement the one-dimensional MFM under the terminal and the spot measure driven by a general diffusion process. Since the existing literature has been focused exclusively on the Gaussian driving processes our algorithms open the scope for new parameterisations. We then prove that the dynamics of the onedimensional MFM are only affected by the time dependence of the driving process, described by a copula, and not by its marginal distributions. We then shift our focus and show that the one-dimensional MFM under the terminal measure is closely related to the one-factor separable local-volatility LMM. Finally, we move our attention to the models of a two-currency economy. We propose a new three-factor model that we calibrate to the domestic and foreign caplet prices and the foreign exchange call options. To maintain the no-arbitrage condition while calibrating to foreign exchange market we propose a predictor-corrector type step. It is our conjecture that the predictor-corrector step converges, thus the model is well defined.

This paper estimates rates of return across the gross wealth distribution in eight European countries. Like differential saving rates, differential rates of return matter for Post Keynesian theory, because they impact the income and wealth distribution and add an explosive element to growth models. We show that differential rates of return matter empirically by merging data on household balance sheets with long-run returns for individual asset categories. We find that (1) the composition of wealth differentiates between three socioeconomic groups: 30% are asset-poor, 65% are middle-class home owners, and the top 5% are business-owning capitalists; (2) rates of return rise across all groups; and (3) rates of return broadly follow a log-shaped function across the distribution, where inequality in the lower half of the distribution is higher than in the upper half. If socioeconomic groups are collapsed into the bottom 95% workers and top 5% capitalists, then rates of return are 5.6% for the former and 7.2% for the latter.
Series: Ecological Economic Papers

In this thesis we use Markov chain Monte Carlo (MCMC) simulation to calibrate a two-factor arbitrage-free model for the term structure of interest rates which is proposed by Cairns (2004a) based on the positive-interest framework (Flesaker and Hughston, 1996). The model is a time-homogeneous model driven by latent state variables which follow a two-dimensional Ornstein-Uhlenbeck process. A number of MCMC algorithms are developed and employed for estimating both model parameters and latent variables where simulated data are used in the first place in order to validate the algorithms and ensure that they can result in reasonable and reliable estimates before using UK market data. Once the posterior estimates are obtained, we next investigate goodness of fit of the model and eventually assess the impact of parameter uncertainty on the forecasting of yield curves in which the achieved MCMC output can be used directly. Additionally, the developed algorithm is also applied for estimating the two-factor Vasicek term structure model for comparison. We conclude that our algorithms work reasonably well for estimating the Cairns term structure model. The model is then fitted to UK Strips data, and it found to produce reasonable fits for medium- and long-term yields, but we also conclude that some improvement may be required for the short-end of the yield curves.

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O objetivo do presente trabalho é verificar se o modelo que combina correção de erros e fatores extraídos de grandes conjuntos de dados macroeconômicos produz previsões mais precisas das taxas de juros do Brasil em relação aos modelos VAR, VECM e FAVAR. Para realizar esta análise, foi utilizado o modelo sugerido por Banerjee e Marcellino (2009), o FAVECM, que consiste em agregar o mecanismo de correção de erros ao modelo proposto por Bernanke, Boivin e Eliasz (2005), o FAVAR. A hipótese é que o FAVECM possuiu uma formulação teórica mais geral. Os resultados mostram que para o mercado brasileiro o FAVECM apresentou ganhos significativos de previsão para as taxas mais longas e horizontes de previsão maiores.
The objective of the present work is to examine if the model that combines error correction and factors extracted from large macoeconomic data sets offers a higher forecasting accuracy of the interest rate in Brazil when compared to VAR, VECM and FAVAR. In order to conduct this analysis it was used the econometric methodology introduced by Banerjee and Marcellino (2009), the FAVECM, which allows for the inclusion of error correction terms in the model introduced by Bernanke, Boivin and Eliasz (2005), the FAVAR. The hypothesis is that the FAVECM has several conceptual advantages given it is a nesting (or has a more general) specification. The results show that, for the Brazilian market, the FAVECM presented significant gains in forecasts for longer maturity rates and for longer prevision horizons.

The fourth edition of this textbook on pricing and hedging of financial derivatives, now also including dynamic equilibrium theory, continues to combine sound mathematical principles with economic applications. Concentrating on the probabilistic theory of continuous time arbitrage pricing of financial derivatives, including stochastic optimal control theory and optimal stopping theory, the book is designed for graduate students in economics and mathematics, and combines the necessary mathematical background with a solid economic focus. It includes a solved example for every new technique presented, contains numerous exercises, and suggests further reading in each chapter. All concepts and ideas are discussed, not only from a mathematics point of view, but the mathematical theory is also always supplemented with lots of intuitive economic arguments. In the substantially extended fourth edition Tomas Björk has added completely new chapters on incomplete markets, treating such topics as the Esscher transform, the minimal martingale measure, f-divergences, optimal investment theory for incomplete markets, and good deal bounds. There is also an entirely new part of the book presenting dynamic equilibrium theory. This includes several chapters on unit net supply endowments models, and the Cox–Ingersoll–Ross equilibrium factor model (including the CIR equilibrium interest rate model). Providing two full treatments of arbitrage theory—the classical delta hedging approach and the modern martingale approach—the book is written in such a way that these approaches can be studied independently of each other, thus providing the less mathematically oriented reader with a self-contained introduction to arbitrage theory and equilibrium theory, while at the same time allowing the more advanced student to see the full theory in action.

The strain rate intensity factor in the theory of rigid perfectly plastic isotropic materials is the coefficient of the principal singular term in a series expansion of the equivalent strain rate in the vicinity of maximum friction surfaces. This coefficient can be used to predict the evolution of material properties in a narrow layer in the vicinity of surfaces where the friction stress is high. Usually, conventional evolution equations are not compatible with the plasticity equations near maximum friction surfaces. It is therefore of interest to extend the theories based on the strain rate intensity factor to more general models than the rigid perfectly plastic isotropic solids. The present paper deals with plane strain deformation of rigid plastic anisotropic material. It is shown by means of a simple analytic solution that the velocity field is singular in the vicinity of maximum friction surfaces. Thus the strain rate intensity factor can be introduced for such materials. An effect of plastic anisotropy on its value is demonstrated. In addition, it is shown that rigid plastic solutions for anisotropic materials can exhibit various types of singularity in the vicinity of maximum friction surfaces, in contrast to isotropic materials where one type only is possible. Nevertheless, in most cases the type of singularity is same for isotropic and anisotropic materials.

The strain rate intensity factor is the coefficient of the principal singular term in a series expansion of the equivalent strain rate in the vicinity of maximum friction surfaces. Such singular behaviour occurs in the case of several rigid plastic models (rigid perfectly plastic solids, the double-shearing model, the double slip and rotation model, some of viscoplastic models). Since it is only possible to introduce the strain rate intensity factor for singular velocity fields, it is obvious that standard finite element codes cannot be used to calculate it. The currently available distributions of the strain rate intensity factor have been found from closed form solutions or with the use of simple approximate solutions (for instance upper bound solutions). Closed form solutions are available for boundary value problems with simple geometry (flow through infinite rough channels, compression of infinite layers between rough plates and so on) and, therefore, are mostly of academic interest. Simple approximate solutions can predict general tendencies in the distribution of the strain rate intensity factor but cannot predict its distribution with a sufficient accuracy for industrial applications. For, the strain rate intensity factor reflects a very local effect inherent in the velocity field whereas simple approximate methods, such as the upper bound method, estimate global parameters, such as the limit load. The purpose of the present research is to propose a special numerical technique for calculating the strain rate intensity factor in the case of plane strain deformation of rigid perfectly plastic materials and to verify it by means of comparison with an analytical solution. The technique is based on the method of Riemann.

GUR1050 is a medical grade variety of ultra-high molecular weight polyethylene (UHMWPE) intended for use on total joint prosthesis and implants. Probes of this material were characterized on a compression test following ASTM norms and lineaments. Available data from these mechanical tests is fitted on multiple material models. Achieved results on numerical solutions of finite element modeling (FEM) of the tests are discussed, looking for the best one available in order to simulate with accuracy GUR1050 behavior, with specific interest on the load curve results, showing the pertinence of using certain models on different conditions. It was found that the use of a bilinear isotropic hardening model assures the best fit for GUR1050 behavior in uniaxial compression under a constant strain rate.

Recent advances in numerical optimization software now allow problems arising in the evaluation of complex centrifugal compressor train performance to be readily solved by machinery users. Analyses of compressor operations often requires consideration of multiple non-linear constraints involving pressure, temperature, flow rate, composition and power. Based on these constraints, the operational boundaries of the machinery must be evaluated. Frequently operating points of greatest interest exist where one of the operational variables, such as flow rate, is maximized subject to operational constraints. A methodology is proposed which can be used to apply commercially available optimization software to problems of this type. A review of gas equation of state relationships needed to determine thermodynamic properties is provided, as well as methods for calculating compressor discharge pressure based on polytropic head and efficiency. Recycle control is considered and a model is proposed.

Micro-scale fluid dynamics has received intensive interest due to the emergence of Micro-Electro-Mechanical Systems (MEMS) technology. Non-circular cross sections are common channel shapes that can be produced through a variety of micro-fabrication techniques. Non-circular microchannels have extensive practical applications in MEMS. Slip flow in noncircular microchannels has been examined by the authors and a review of several new models obtained by the authors is presented. These models are general and robust, and can be used by the research community for practical engineering design of microchannel flow systems. The reviewed models address: (i) fully developed slip flow in non-circular microchannels, (ii) hydrodynamically developing slip flow in non-circular microchannels, (iii) compressibility effects, and (iv) roughness effects. A model is proposed to predict the friction factor and Reynolds product fRe for fully developed and developing slip flow in most non-circular micro-channels. Compressibility effects on slip flow in non-circular microchannels have been examined and simple models are proposed to predict the pressure distribution and mass flow rate for slip flow in most non-circular microchannels. Finally, the effect of corrugated surface roughness on fully developed laminar flow in microtubes is examined. Simple analytical models are developed to predict friction factor and pressure drop in corrugated rough microtubes for continuum flow and slip flow.

Gaseous flow in circular and noncircular microchannels has been examined and a simple analytical model with second-order slip boundary conditions for normalized Poiseuille number is proposed. The model is applicable to arbitrary length scale. It extends previous studies to the transition regime by employing the second-order slip boundary conditions. The effects of the second-order slip boundary conditions are analyzed. As in slip and transition regimes, no solutions or graphical and tabulated data exist for most geometries, the developed simple model can be used to predict friction factor, mass flow rate, tangential momentum accommodation coefficient, pressure distribution of gaseous flow in noncircular microchannels by the research community for the practical engineering design of microchannels such as rectangular, trapezoidal, double-trapezoidal, triangular, rhombic, hexagonal, octagonal, elliptical, semielliptical, parabolic, circular sector, circular segment, annular sector, rectangular duct with unilateral elliptical or circular end, annular, and even comparatively complex doubly-connected microducts. The developed second-order models are preferable since the difficulty and “investment” is negligible compared with the cost of alternative methods such as molecular simulations or solutions of Boltzmann equation. Navier-Stokes equations with second-order slip models can be used to predict quantities of engineering interest such as Poiseuille number, tangential momentum accommodation coefficient, mass flow rate, pressure distribution, and pressure drop beyond its typically acknowledged limit of application. The appropriate or effective second-order slip coefficients include the contribution of the Knudsen layers in order to capture the complete solution of the Boltzmann equation for the Poiseuille number, mass flow rate, and pressure distribution. It could be reasonable that various researchers proposed different second-order slip coefficients because the values are naturally different in different Knudsen number regimes. The transition regime is a varying mixture of different transport mechanisms and the mixed degree relies on the magnitude of the Knudsen number. It is analytically shown that the Knudsen’s minimum can be predicted with the second-order model and the Knudsen value of the occurrence of Knudsen’s minimum depends on inlet and outlet pressure ratio. The compressibility and rarefaction effects on mass flow rate and the curvature of the pressure distribution by employing first-order and second-order slip flow models are analyzed and compared. The condition of linear pressure distribution is given. This paper demonstrates that with some relatively simple ideas from knowledge, observation, and intuition, one can predict some fairly complex flows.

Abstract Numerical experiments were performed to assess the effect of numerical discretization error on the convergence rate of polynomial chaos (PC) approximations for a transonic axial compressor stage. A random variable with a uniform distribution and expected value of one was introduced into the expression for turbulent viscosity of the k-ω SST turbulence model. Model uncertainty was quantified from the expected value and standard deviation estimates obtained via univariate non-intrusive polynomial chaos. Spectral projection and point collocation were both used and their results were compared. The effect of discretization error on convergence of the PC approximation was investigated using a grid refinement study with four grids. The PC expansion was computed for each grid while maintaining the same boundary conditions, basis functions, model evaluations, random variable distribution, and polynomial order. The quantities of interest (QOIs) were total–to–total pressure ratio, total–to–total temperature, and adiabatic efficiency. The grid resolution was found to have an influence on resulting surrogate models and the estimates of expected value and standard deviation for all QOIs. However, the estimates converged towards final values as the mesh was refined. Point collocation provided different estimates from spectral projection and the difference was also found to depend on the mesh size.

A robust optimization scheme, known as rkmGen, for reaction rate parameter estimation has been developed for the generation of reduced kinetics models of practical interest for reactive flow simulations. It employs a stochastic optimization algorithm known as Simulated Annealing, and is implemented in C++ and coupled with Cantera, a chemical kinetics software package, to automate the reduced kinetic mechanism generation process. Reaction rate parameters in reduced order models can be estimated by optimizing against target data generated from a detailed model or by experiment. Target data may be of several different kinds: ignition delay time, blow-out time, laminar flame speed, species time-history profiles and species reactivity profiles. The software allows for simultaneous optimization against multiple target data sets over a wide range of temperatures, pressures and equivalence ratios. In this paper, a detailed description of the optimization strategy used for the reaction parameter estimation is provided. To illustrate the performance of the software for reduced kinetic development, a number of test cases for various fuels were used: one-step, three-step and four-step global reduced kinetic models for ethylene, Jet-A and methane, respectively, and a fifty-step semi-global reduced kinetic model for methane. The fifty-step semi-global reduced kinetic model was implemented in the Star*CCM+ commercial CFD code to simulate Sandia Flame D using laminar flamelet libraries and compared with the experimental data. Simulations were also performed with the GRI3.0 mechanism for comparisons.

Abstract One of the major efforts in Oil and Gas industry's digital transformation is the increased use of data in optimizing processes. This paper focuses on optimizing the process of section-milling during well abandonment by leveraging data gathered from past section-milling cycles. Several mathematical model-based techniques have been presented in recent years for improving the rate of penetration (ROP) in section-milling. However, only a few data-driven methodologies have been adopted in this field of interest, most likely due to unavailability of data. A trainingsubset of field data from section-milling operations is used for developing a range of machine learning models. Performance of these models is then evaluated using mean absolute percentage error (MAPE) against testing subset of data.

Abstract Many structures are subjected to varying forces, moving boundaries, and other dynamic conditions. Whether part of a vehicle, building, or active energy mitigation device, data on such changes can represent useful knowledge, but also presents challenges in its collection and analysis. In systems where changes occur rapidly, assessment of the system’s state within a useful time span is required to enable an appropriate response before the system’s state changes further. Rapid state estimation is especially important but poses unique difficulties. In determining the state of a structural system subjected to high-rate dynamic changes, measuring the frequency response is one method that can be used to draw inferences, provided the system is adequately understood and defined. The work presented here is the result of an investigation into methods to determine the frequency response, and thus state, of a structure subjected to high-rate boundary changes in real-time. In order to facilitate development, the Air Force Research Laboratory created the DROPBEAR, a testbed with an oscillating beam subjected to a continuously variable boundary condition. One end of the beam is held by a stationary fixed support, while a pinned support is able to move along the beam’s length. The free end of the beam structure is instrumented with acceleration, velocity, and position sensors measuring the beam’s vertical axis. Direct position measurement of the pin location is also taken to provide a reference for comparison with numerical models. This work presents a numerical investigation into methods for extracting the frequency response of a structure in real-time. An FFT based method with a rolling window is used to track the frequency of a data set generated to represent the range of the DROPBEAR, and is run with multiple window lengths. The frequency precision and latency of the FFT method is analyzed in each configuration. A specialized frequency extraction technique, Delayed Comparison Error Minimization, is implemented with parameters optimized for the frequency range of interest. The performance metrics of latency and precision are analyzed and compared to the baseline rolling FFT method results, and applicability is discussed.

After adopting an inflation targeting framework for monetary policy at the turn of the century, the Central Bank of Colombia started actively using the monetary policy interest rate as its key policy tool. In this regard, this paper examines the interest rate pass-through from the monetary policy rate to the retail rates in Colombia and explores asymmetries in the adjustment process within the framework of a non-linear version of the ARDL (NARDL) model developed by Shin et al. (2014). Our findings show that the policy rate plays a key role in determining deposit and lending retail rates but the nature of the pass-through varies across different types of lending products. In the case of lending rates, the pass-through is usually a full one, and takes around 12 months to be nearly complete. Our results capture an asymmetric positive pass-through in deposit rates and an upward rigidity in the lending rates of consumer and ordinary corporate loans, key segments of the credit market. These findings imply that most retail lending rates respond more to policy rate cuts than to hikes, indicating that financial intermediaries are more reluctant to raise interest rates than to decrease them following policy adjustments.

We use a total survey error approach to examine and make recommendations on how to adjust for non-sampling error in longitudinal, mixed-mode surveys. Using data from the National Crime Victimization Survey (NCVS), we examine three major sources of non-sampling error: telescoping, mode effects, and fatigue. We present an assessment of each source of error from a total survey error perspective and propose alternative adjustments to adjust better for this error. Findings suggest that telescoping and fatigue are likely sources of error in the NCVS, but the use of mixed-modes is not. Furthermore, both telescoping and fatigue are present in longitudinal surveys and accounting for one but not the other results in estimates that under- or overestimate the measures of interest—in this case, the rate of crime in the United States.

Background: Clear allergen communication in food business operators (FBOs) has been shown to have a positive impact on customers’ perceptions of businesses (Barnett et al., 2013). However, the precise size and nature of this effect is not known: there is a paucity of quantitative evidence in this area, particularly in the form of randomised controlled trials (RCTs). The Food Standards Agency (FSA), in collaboration with Kantar’s Behavioural Practice, conducted a feasibility trial to investigate whether a randomised cluster trial – involving the proactive communication of allergen information at the point of sale in FBOs – is feasible in the United Kingdom (UK). Objectives: The trial sought to establish: ease of recruitments of businesses into trials; customer response rates for in-store outcome surveys; fidelity of intervention delivery by FBO staff; sensitivity of outcome survey measures to change; and appropriateness of the chosen analytical approach. Method: Following a recruitment phase – in which one of fourteen multinational FBOs was successfully recruited – the execution of the feasibility trial involved a quasi-randomised matched-pairs clustered experiment. Each of the FBO’s ten participating branches underwent pair-wise matching, with similarity of branches judged according to four criteria: Food Hygiene Rating Scheme (FHRS) score, average weekly footfall, number of staff and customer satisfaction rating. The allocation ratio for this trial was 1:1: one branch in each pair was assigned to the treatment group by a representative from the FBO, while the other continued to operate in accordance with their standard operating procedure. As a business-based feasibility trial, customers at participating branches throughout the fieldwork period were automatically enrolled in the trial. The trial was single-blind: customers at treatment branches were not aware that they were receiving an intervention. All customers who visited participating branches throughout the fieldwork period were asked to complete a short in-store survey on a tablet affixed in branches. This survey contained four outcome measures which operationalised customers’: perceptions of food safety in the FBO; trust in the FBO; self-reported confidence to ask for allergen information in future visits; and overall satisfaction with their visit. Results: Fieldwork was conducted from the 3 – 20 March 2020, with cessation occurring prematurely due to the closure of outlets following the proliferation of COVID-19. n=177 participants took part in the trial across the ten branches; however, response rates (which ranged between 0.1 - 0.8%) were likely also adversely affected by COVID-19. Intervention fidelity was an issue in this study: while compliance with delivery of the intervention was relatively high in treatment branches (78.9%), erroneous delivery in control branches was also common (46.2%). Survey data were analysed using random-intercept multilevel linear regression models (due to the nesting of customers within branches). Despite the trial’s modest sample size, there was some evidence to suggest that the intervention had a positive effect for those suffering from allergies/intolerances for the ‘trust’ (β = 1.288, p<0.01) and ‘satisfaction’ (β = 0.945, p<0.01) outcome variables. Due to singularity within the fitted linear models, hierarchical Bayes models were used to corroborate the size of these interactions. Conclusions: The results of this trial suggest that a fully powered clustered RCT would likely be feasible in the UK. In this case, the primary challenge in the execution of the trial was the recruitment of FBOs: despite high levels of initial interest from four chains, only one took part. However, it is likely that the proliferation of COVID-19 adversely impacted chain participation – two other FBOs withdrew during branch eligibility assessment and selection, citing COVID-19 as a barrier. COVID-19 also likely lowered the on-site survey response rate: a significant negative Pearson correlation was observed between daily survey completions and COVID-19 cases in the UK, highlighting a likely relationship between the two. Limitations: The trial was quasi-random: selection of branches, pair matching and allocation to treatment/control groups were not systematically conducted. These processes were undertaken by a representative from the FBO’s Safety and Quality Assurance team (with oversight from Kantar representatives on pair matching), as a result of the chain’s internal operational restrictions.

Increased production rates and cost reduction are affecting manufacturing in all sectors of the mobility industry. One enabling methodology that could achieve these goals in the burgeoning “Industry 4.0” environment is the deterministic assembly (DA) approach. The DA approach is defined as an optimized assembly process; it always forms the same final structure and has a strong link to design-for-assembly and design-for-automation methodologies. It also looks at the whole supply chain, enabling drastic savings at the original equipment manufacturer (OEM) level by reducing recurring costs and lead time. Within Industry 4.0, DA will be required mainly for the aerospace and the space industry, but serves as an interesting approach for other industries assembling large and/or complex components. In its entirety, the DA approach connects an entire supply chain—from part manufacturing at an elementary level to an OEM’s final assembly line level. Addressing the whole process of aircraft design and manufacturing is necessary to develop further collaboration models between OEMs and the supply chain, including addressing the most pressing technology challenges. Since all parts aggregate at the OEM level, the OEM—as an integrator of all these single parts—needs special end-to-end methodologies to drastically decrease cost and lead time. This holistic approach can be considered in part design as well (in the design-for-automation and design-for-assembly philosophy). This allows for quicker assembly at the OEM level, such as “part-to-part” or “hole-to-hole” approaches, versus traditional, classical assembly methods like manual measurement or measurement-assisted assembly. In addition, it can increase flexibility regarding rate changes in production (such as those due to pandemic- or climate-related environmental challenges). The standardization and harmonization of these areas would help all industries and designers to have a deterministic approach with an end-to-end concept. Simulations can easily compare possible production and assembly steps with different impacts on local and global tolerances. Global measurement feedback needs high-accuracy turnkey solutions, which are very costly and inflexible. The goal of standardization would be to use Industry 4.0 feedback and features, as well as to define several building blocks of the DA approach as a one-way assembly (also known as one-up assembly, or “OUA”), false one-way assembly, “Jig-as-Master,” etc., up to the hole-to-hole assembly approach. The evolution of these assembly principles and the link to simulation approaches are undefined and unsolved domains; they are discussed in this report. They must be discussed in greater depth with aims of (first) clarifying the scope of the industry-wide alignment needs and (second) prioritizing the issues requiring standardization. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.

This technical report presents two applications of the GenCade model to simulate long-term shoreline evolution along the Delaware Coast driven by waves, inlet sediment transport, and longshore sediment transport. The simulations also include coastal protection practices such as periodic beach fills, post-storm nourishment, and sand bypassing. Two site-specific GenCade models were developed: one is for the coasts adjacent to the Indian River Inlet (IRI) and another is for Fenwick Island. In the first model, the sediment exchanges among the shoals and bars of the inlet were simulated by the Inlet Reservoir Model (IRM) in the GenCade. An inlet sediment transfer factor (γ) was derived from the IRM to quantify the capability of inlet sediment bypassing, measured by a rate of longshore sediments transferred across an inlet from the updrift side to the downdrift side. The second model for the Fenwick Island coast was validated by simulating an 11-y ear-long shoreline evolution driven by longshore sediment transport and periodic beach fills. Validation of the two models was achieved through evaluating statistical errors of simulations. The effects of the sand bypassing operation across the IRI and the beach fills in Fenwick Island were examined by comparing simulation results with and without those protection practices. Results of the study will benefit planning and management of coastal sediments at the sites.

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%.