初探 Amihud 流動性指標對景氣循環之預測力

Bayesian dynamic probit models for the analysis of longitudinal data

Storm tide (combination of storm surge and the astronomical tide) flooding is a natural hazard with significant global social and economic consequences. For this reason, government agencies and stakeholders need storm tide flood maps to determine population and infrastructure at risk to present and future levels of inundation. Computer models of varying complexity are able to produce regional-scale storm tide flood maps and current model types are either static or dynamic in their implementation. Static models of storm tide utilize storm tide heights to inundate locations hydrologically connected to the coast, whilst dynamic models simulate physical processes that cause flooding. Static models have been used in regional-scale storm tide flood impact assessments, but model limitations and coarse spatial resolutions contribute to uncertain impact estimates. Dynamic models are better at estimating flooding and impact but are computationally expensive. In this study we have developed a dynamic reduced-complexity model of storm tide flooding that is computationally efficient and is applied at hyper-resolutions (<100 m cell size) over regional scales. We test the performance of this dynamic reduced-complexity model and a separate static model at three test sites where storm tide observational data are available. Additionally, we perform a flood impact assessment at each site using the dynamic reduced-complexity and static model outputs. Our results show that static models can overestimate observed flood areas up to 204 % and estimate more than twice the number of people, infrastructure, and agricultural land affected by flooding. Overall we find that that a reduced-complexity dynamic model of storm tide provides more conservative estimates of coastal flooding and impact.

The article presents a dynamic stochastic general equilibrium model (DSGE-model) for the Russian economy. The model describes the behavior of the following macroeconomic agents: households, real sector, banking sector, Central Bank, as well as the interactions between them and the world. Household modeling uses the external habit formation approach to account for the inertia of preferences. To model the real sector, we abandoned the most common approach which assumes that the decision on investments is made by the households as the owners of production factors. Instead, we took the firm-specific capital approach which assumes that the decision on investment is made by the firms themselves. The study also considers that in Russia, fixed assets are mostly invested from the firms' own funds. To account for the investment inertia in the fixed asset in a real sector model, the expenditures are transferred to the commissioning of new facilities, the Calvo model is applied to describe the price setting under the monopolistic competition. A banking sector which defines the loan and debt interest rates to the key Central Bank interest rate is chosen to be a link between the households and firms in the model. The Taylor equation is used to describe the monetary policy of the Bank of Russia under the inflation targeting, while an inertia factor is included into the equation with the uncovered interest parity for the budget rule which regulates the purchases (or sales) of the currency by the National Welfare Fund. The final linearized model is a system of 23 difference equations with rational expectations. Based on the proposed model, calculations were made and key macroeconomic indicators were forecasted for 2020–2021 on a quarterly basis for the Russian economy. The calculations account for the relevant recessionary factors: oil price fall, oil production cut in OPEC+ deals, quarantine measures aimed to prevent the spread of the corona virus infection, anti-recessionary measures of the RF Government. The findings show that the economic downturn in 2020 can be from 5 to 7% under COVID-19 pandemic. Growth in 2021 is estimated to be within 3–5%. The developed model can be used for scenario projecting for the Russian economy, upgrading the monetary policy of the Bank of Russia, and for developing applied quarterly projection models (QPM). The model could be further modified by including more elements: decomposing the household sector into the Ricardian and non-Ricardian ones, identifying the resources industries and industries in the real sector which manufacture the invested goods, including the key taxes and budget expenses into the model. One more promising area is to analyze the equilibrium of the interest rates when large firms could accumulate their own financial resources. This prerequisite decreases the demand for the bank loans from the real sector and, thus, leads to lower, including the negative, interest rates. The proposed approach enhances the quality of a DSGE model as a predictive tool for making the political and managerial decisions.

In digitally controlled DC-DC converters with a single voltage feedback loop, the two quantizers, namely the A/D converter and the digital pulse-width modulator (DPWM), can cause undesirable limit-cycle oscillations. In this paper, static and dynamic models that include the quantization effects are derived and used to explain the origins of limit-cycle oscillations. In the static model, existence of DC solution, which is a necessary no-limit-cycle condition, is examined using a graphical method. A concept of amplitude and offset dependent gain is introduced to extend the describing function method and derive the dynamic system model. From the static and dynamic models, no-limit-cycle conditions associated with A/D, DPWM and compensator design criteria are derived. The conclusions are illustrated by simulation and experimental examples.

In digitally controlled dc-dc converters with a single voltage feedback loop, the two quantizers, namely the analog-to-digital (A/D) converter and the digital pulse-width modulator (DPWM), can cause undesirable limit-cycle oscillations. In this paper, static and dynamic models that include the quantization effects are derived and used to explain the origins of limit-cycle oscillations. In the static model, existence of dc solution, which is a necessary no-limit-cycle condition, is examined using a graphical method. Based on the generalized describing function method, the amplitude and offset-dependent gain model of a quantizer is applied to derive the dynamic system model. From the static and dynamic models, no-limit-cycle conditions associated with A/D, DPWM and compensator design criteria are derived. The conclusions are illustrated by simulation and experimental examples

Purpose The purpose of this paper is to test the existence of true persistence in the generation and adoption of product innovations in the context of a developing country. Design/methodology/approach A dynamic probit model with random effects is used to test true persistence relying on a panel data set constructed from three waves of the Colombian innovation survey (Encuesta de Desarrollo e Innvovación Tecnológica) covering the time span from 2003 to 2008. Findings This paper empirically shows the existence of true innovation persistence for two of the three types of product innovation studied: the adoption of product innovation that is new to the firm; and the adoption of product innovation that is new to the national market. However, the study could not confirm true persistence in the generation of product innovation. Originality/value To the best of our knowledge, this is the first study that systematically tests innovation persistence differentiating between the adoption of innovations that are new to the firm and innovation that is new to the national market. It is also the first study in this research area that uses a dynamic probit model with random effects according to the original specification by Wooldridge (2005).

As the main cause of large blackouts, understanding the complex interactions involved in cascading failure propagation is a critical area of ongoing research. The static model of cascading failures is a well-accepted method to investigate the cascading effects in power systems. However, as the power system evolves, dynamic behaviours become more variable, it is necessary to evaluate the validity of the assumptions in the static model. This paper compares and validates a conventional static model with a novel dynamic model capturing frequency dynamics. N-2 contingency analysis is used to trigger cascading events and the unserved demand and the number of branch outages are used as metrics. Analysis using the 39-bus, 200-bus and 2000-bus benchmark systems reveal similarities and differences between the static and dynamic models and reveal, for the first time, how these differences vary as network size grows. Sensitivity analysis on system dispatch capabilities provides some initial guidance to help reduce the differences between models and helps with understanding of the relative importance of cascading mechanisms.

1. Introduction The onset of the current economic downturn following the longest expansion in U.S. history has renewed interest in the role of automatic stabilizers designed to insure households against negative cyclical income shocks. This system of income and consumption stabilizers includes, among others, the individual income tax and the panoply of social insurance programs, such as unemployment insurance and the Food Stamp Program. While the income tax and unemployment insurance have received recent attention (Gruber 1997; Auerbach and Feenberg 2000; Kniesner and Ziliak 2002a, b), little is known about the role of food stamps as an automatic stabilizer even though the program served over 27 million Americans at its peak in 1994. This gap in the literature is particularly acute in light of passage of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (Welfare Reform Act), which introduced new rules on cash-assistance recipients and thus the nearly half of food stamp recipients who also receive cash welfare. Moreover, the 1996 welfare reform also had a direct administrative effect on the Food Stamp Program by ending the eligibility of some recipients, reducing average benefit levels, and requiring states to replace paper coupons with Electronic Benefit Transfer cards. Importantly, the Welfare Reform Act also eliminated the entitlement status of the main cash-welfare program, Aid to Families with Dependent Children (AFDC), thus positioning food stamps as a more prominent countercyclical consumption stabilizer. A first task in assessing the possible stabilization role of food stamps in the era of welfare reform is to identify the cyclical sensitivity of food stamp caseloads. If food stamp caseloads are acyclical, then we would expect no role for food stamps in smoothing consumption over the business cycle. If, however, food stamp caseloads are highly cyclical, then food stamps may function as an important antirecessionary tool. By the same token, the new welfare policies may independently affect food stamp caseload movements and interact with the business cycle, thereby altering the possible stabilization role of the program. In this paper, we specify a dynamic model of food stamp caseloads to estimate the responsiveness of the caseload to the business cycle, to welfare policies, and to interactions between the business cycle and welfare policies. Unlike cash welfare, there has been scant research on the cyclicality of food stamp caseloads.1 Wallace and Blank (1999) are a recent exception in their use of both static annual and dynamic monthly food stamp caseload models based on state-level panel data for the 1980 to 1998 federal fiscal years. With annual data, food stamp caseloads were strongly countercyclical, and reform of AFDC led to weak declines in total caseloads.2 Specifically, they attribute up to 44% of the 1994 to 1998 food stamp caseload decline to economic conditions and about 6% of the decline to welfare reform. They reach broadly similar conclusions with monthly data. However, Wallace and Blank calculate that upward of 85% of the post-1996 decline in food stamp caseloads can be attributed to welfare reform if one is willing to ascribe all the unexplained residual to welfare reform, which as the authors note is undoubtedly an overestimate of welfare reform's effect on food stamp caseloads (p. 85). In their static models, Figlio, Gundersen, and Ziliak (2000) reached conclusions similar to Wallace and Blank's estimates with annual-level data. In their preferred dynamic models, they attribute about 35% of the 1994 to 1998 caseload decline to the macroeconomy and virtually nothing to welfare reform. We improve on this previous research on food stamp caseloads along several dimensions. First, we not only follow other research in estimating the impact of AFDC policy changes on food stamp caseloads but also examine the impact of policies that are focused directly on food stamps. …

Integration of dynamic and static modeling on guided inquiry learning can help students to understand chemical concepts at macroscopic, symbolic and microscopic levels. This research aimed to examine and to explain the differences of students’ multiple representation ability that was taught by guided inquiry with dynamic and static modeling in redox reaction concept. This research used descriptive and quasi-experimental design. Data were analyzed using descriptive and manova statistics analysis. The results showed that the ability of students’ macroscopic level that was taught by guided inquiry with dynamic and static modeling is the same. While the student’s symbolic and microscopic level ability that was taught by guided inquiry with dynamic modeling higher than student’s ability that was taught by guided inquiry with static modeling. The implication of this research is chemistry learning with dynamic modeling can help students to construct chemical concept more easily and gain the complete understanding.

BackgroundThis paper compares cost-effectiveness results from two models of maternal immunization to prevent pertussis in infants in Brazil, one static, one dynamic, to explore when static models are adequate for public health decisions and when the extra effort required by dynamic models is worthwhile. MethodsWe defined two scenarios to explore key differences between static and dynamic models, herd immunity and time horizon. Scenario 1 evaluates the incremental cost/DALY of maternal acellular pertussis (aP) immunization as routine infant vaccination coverage ranges from low/moderate up to, and above, the threshold at which herd immunity begins to eliminate pertussis. Scenario 2 compares cost-effectiveness estimates over the models’ different time horizons. Maternal vaccine prices of $9.55/dose (base case) and $1/dose were evaluated. ResultsThe dynamic model shows that maternal immunization could be cost-saving as well as life-saving at low levels of infant vaccination coverage. When infant coverage reaches the threshold range (90–95%), it is expensive: the dynamic model estimates that maternal immunization costs $2 million/DALY at infant coverage > 95% and maternal vaccine price of $9.55/dose; at $1/dose, cost/DALY is $200,000. By contrast, the static model estimates costs/DALY only modestly higher at high than at low infant coverage. When the models’ estimates over their different time horizons are compared at infant coverage < 90–95%, their projections fall in the same range. ConclusionsStatic models may serve to explore an intervention’s cost-effectiveness against infectious disease: the direction and principal drivers of change were the same in both models. When, however, an intervention too small to have significant herd immunity effects itself, such as maternal aP immunization, takes place against a background of vaccination in the rest of the population, a dynamic model is crucial to accurate estimates of cost-effectiveness. This finding is particularly important in the context of widely varying routine infant vaccination rates globally. Clinical Trial registryClinical Trial registry name and registration number: Not applicable.

PurposeContinuum robots modeling, be it from a hard or soft class, is giving rise to several challenges compared with rigid robots. These challenges are mainly due to kinematic redundancy, dynamic nonlinearity and high flexibility. This paper aims initially at designing a hard class of continuum robots, namely, cable-driven continuum robot (CDCR) and equally at developing their kinematic and dynamic models.Design/methodology/approachFirst, the CDCR prototype is constructed, and its description is made. Second, kinematic models are established based on the constant curvature assumption and inextensible bending section. Third, by using the Lagrange method, the dynamic model is derived under some simplifications and based on the kinematic equations, in which the flexible backbone’s elasticity modulus was identified experimentally. Finally, the static model of the CDCR is also derived based on the dynamic model.FindingsNumerical examples are carried out using Matlab software to verify the static and dynamic models. Moreover, the static model is validated by comparing the simulation’s results to the real measurements that have been provided with satisfactory results.Originality/valueTo reduce the complexity of the dynamic model’s expressions and avoid the numerical singularity when the bending angle is close to zero, some simplifications have been taken, especially for the kinetic energy terms, by using the nonlinear functions approximation. Hence, the main advantage of this analytical-approximate solution is that it can be applied in the bending angle that ranges up to 2p with reasonable errors, unlike the previously proposed techniques. Furthermore, the resulting dynamic model has, to some extent, the proprieties of simplicity, accuracy and fast computation time. Ultimately, the obtained results from the simulations and real measurements demonstrate that the considered CDCR’s static and dynamic models are feasible.

Maximizing the Effectiveness of Integrated Reservoir Studies: Practical Approaches to Improving the Process and Results

This paper aimed to apply (dynamic and static) actuarial models to calculate the balanced contribution rates for the planned (at the minimum age) retirement benefit of the General Social Security System, based on the original and substitutive texts of the reform proposed by Michel Temer’s government. Even with the regular increases in life expectancy and the long-term nature of the analyses, national studies on social security are typically based on the static mortality hypothesis. The relevance of this study is evident due to the demographic changes, particularly the increase in life expectancy, experienced by the Brazilian population in recent decades and which put in question the sustainability of the national pension system. The use of dynamic actuarial models allows for more accurate discussions about the future of social security, besides contributing to the still scarce national literature. Static and dynamic actuarial models were applied to a representative individual, adjusting mortality tables from the United Nations covering 1950 to 2100. It was verified that the actuarially fair rates calculated by the dynamic actuarial model are typically higher than those obtained by the static model, especially for women. This difference is expected to increase as gains in life expectancy become more influenced by the reduction in mortality at more advanced ages. Moreover, if the social security reform is approved (in accordance with either the original or the substitutive text), there are indications from the dynamic model that the contributions rates currently charged would be excessive for men. In turn, these rates would be excessive for women considering the original text, and closer to the actuarially fair value considering the substitutive text. The development, disclosure, and regular updating of official dynamic tables (whether for mortality or other biometric assumptions) are also recommended.

Modeling travelers’ mode choice behavior is an important component of travel demand studies. In an effort to account for day-to-day dynamics of travelers’ mode choice behavior, the current study develops a dynamic random effects logit model to endogenously incorporate the mode chosen for a day into the utility function of the mode chosen for the following day. A static multinomial logit model is also estimated to examine the performance of the dynamic model. Per the results, the dynamic random effects model outperforms the static model in relation to predictive power. According to the accuracy indices, the dynamic random effects model offers the predictive power of 60.0% for members of car-deficient households, whereas the static model is limited to 43.1%. Also, comparison of F1-scores indicates that the predictive power of the dynamic random effects model with respect to active travels is 47.1% whereas that of the static model is as low as 15.0%. The results indicate a significant day-to-day dynamic behavior of transit users and active travelers. This pattern is found to be true in general, but not for members of car-deficient households, who are found more likely to choose the same mode for two successive days.

This paper describes the proposed re-development of the Galapagos Field, comprising the abandoned NW Hutton field and the Darwin discovery (Block 211/27 UKCS) which forms a southerly extension. The paper covers the initial concept and analytical evaluation, the static uncertainty model build, the dynamic model history-match, the iterations between static and dynamic modelling, the development subsea and well locations, the optimisation workflow of the advanced Flow Control Valve (FCV) completions in both producers and injectors and the facilities constraints. The redevelopment plan involved several multi-disciplinary teams. 20 years of production data from 52 wells were analysed to identify the production behaviour and confirm the significant target that provided the basis for the development concept selection. The full Brent sequence compartmentalised stochastic static model was based on reprocessed seismic plus 14 exploration and appraisal wells. Streamlines, uncertainty sensitivities and mostly good detective work honed a history match to RFT, BHP, PLT and oil and water production. P50, P90/P10 models were selected and over 100 FCVs optimised to deliver the profiles against an identified FSPO facilities’ constraints. Over 1,000 static models were delivered consisting of sheet sands, incised valleys and channels in heterolithic facies overprinted by a depth trend with appropriate uncertainty ranges. The high well count gave a tight STOIIP probabilistic range of 790/883/937 million stb. The early RFTs illustrated extreme differential depletion between Brent zones and subzones of the Ness. To history-match these the dynamic model retained the static model definition in the Upper Ness to capture the thin but extensive shales. The early 18-month depletion and the late steady production-injection phases were simulated separately in prediction mode and matched the Production Analysis estimated ‘future’ production giving confidence to the history matched model. The initial concept development of 4 subsea-centres, to cover the large field area, with an injector in each compartment proved a robust selection. The horizontal wells increase PI where needed and mitigate internal faulting. The optimisation of the FCVs significantly increased oil production from all zones and drastically reduced water injection and production so that the identified FPSO modifications were relatively modest. The final First Stage Field Development Plan consists of 11 producers and 6 injectors across developed and undeveloped areas confirmed robust P50 reserves of 84 million boe. Robust concept selection allowed for early identification of production units so that constraints and modifications could be accounted for within the economic model. The Galapagos field re-development plan is an excellent example of how detailed static and fully history matched dynamic models can lay the foundations for new technology like the optimisation of the FCVs to access bypassed reserves using significantly smaller production units with reduced requirements for power, compression, gas lift, pumping pressure, injection and production. In short, they shrank the facilities.