Preemptive Policy Research Articles

Can the Phillips curve provide answers to current high inflation rates

Motivated by the weak response of the inflation rate to the tight labor market, the Federal Reserve (Fed) Bank stepped away from its longstanding preemptive policy to fight inflation as the economy approached full employment. This paper aims to reevaluate the relationships of four measures of inflation with the unemployment rate. We accomplish this task by allowing the Phillips curve (PC) slope to vary over time and depend on the magnitude of the unemployment gap. Assessed by both PC convex specification assessment and the Markov chain Monte Carlo (MCMC) estimation method, we confirm the convexity of the PC when the unemployment gap is negative. In addition, we show that the slope of the PC more than doubled when we allow the coefficient on the economic slack to vary over time. Thus, our study shows that PC is still a relevant tool for guiding monetary policy.

Can Text-Based Statistical Models Reveal Impending Banking Crises?

AbstractThis paper introduces statistical models Wordscores and Wordfish to study and predict banking crises. While Wordscores is akin to supervised learning, Wordfish is analogous to unsupervised learning. Both methods estimate the position of banking distress on a tranquil-to-crisis spectrum. Findings suggest that the two statistical methods signal banking crisis up to two-years in advance, with robust results from AUROC, Granger causality and VAR impulse responses. Both methods outperform random forests in predicting crises using textual data. The Wordscores index highlights increased usage of banking sector nomenclature two years preceding a crisis, and Granger causes a crisis series with one and two lag lengths. Results from the Wordfish technique, a statistical model with Poisson distribution, show the index spikes before and during the Global Financial Crisis, when a large share of the countries in the world encountered banking crises. This paper contributes to literature on text-based models of banking crises by bolstering the preemptive policy responses available to policy makers. Given their early warning signals, both Wordscores and Wordfish can be considered a part of the toolset to monitor the stability and resilience of the banking sector.

Enhancing the horizon scanning utility of futures-oriented systematic and scoping reviews

We propose modifications for scoping (and by extension systematic) review methodologies to improve their contribution to horizon scanning exercises. As a means of systematically collecting, coding and synthesising literature, we argue that scoping reviews are ideal for conducting initial environmental scans of a topic of interest, trend analyses and scenario developments. To demonstrate this utility, this paper uses a futures-oriented scoping review of technology-enhanced money laundering and terrorist financing risks as an example. At the forefront of the proposed modifications is a quality assessment framework assessing reviewed publications for their neutrality, evidence, relevance and clarity (NERC). This proposed framework is not only ideal for appraising publications but also as an indication of likelihood, namely whether their discussed insights constitute possible, plausible or probable alternative futures. The validity of the NERC framework in achieving these aims is assessed successfully through statistical correlation tests. The overall aim of this paper is to motivate the proposed modifications, the NERC framework and (modified) scoping reviews more generally as a formidable tool for informing horizon scanning, decision-making and pre-emptive policy development.

The pragmatics of communicating threat and constructing the future in the discourse of the Iranian Supreme Leader

Abstract The paper aims at studying how the discourse of the Iranian Supreme Leader communicates threat and how it presents the reality of Iran’s future in light of policy options. Our data comes from 50 speeches of the Iranian Supreme Leader, delivered between 2005–2020. Adopting the Proximisation Theory, we indicate that spatial and axiological threats are conceptualised in the SL’s discourse as encroaching upon the present and future to impact the Islamic Republic of Iran. But, at the same time, the SL’s discourse depicts the impact consequences as relatively remote from Iran’s present and possible to materialise in the future space provided that certain preliminary circumstances are fulfilled. In this regard, aiming to neutralise the construed threats, the SL’s discourse depicts the privileged vision of the future space involving hortatory preemptive policies. We indicate that the SL’s discourse employs the construal of threats to necessitate and justify taking up future-building preemptive policies.

Juridical Study of Article 43a in Amending Law Number 5 of 2018 Concerning Criminal Acts of Terrorism in Pre-Emptive Strike Policy

Finding out the effects of terrorist activities in Indonesia and the application of Law Number 5 of 2018 concerning Criminal activities of Terrorism Article 43A Against Strike Pre-Emptive Policies are the goals of the research. The research approach used is normative juridical, meaning that it is based on the primary legal literature and is carried out by looking at relevant laws, regulations, theories, and conceptions. Examining Law Number 5 of 2018 concerning Amendments to Law 15 of 2003 concerning the Eradication of Criminal Acts of Terrorism is the goal of the study. The amendment to Article 43A, which inserts and reads in the framework of dealing with Criminal Acts of Terrorism, contains dangerous articles. It is unclear what is meant by countermeasures, every certain person, allegedly brought or placed and a certain place. These are the results of the discussion in Law Number 5 of 2018 concerning Amendments to Law 15 of 2003 concerning the Eradication of Criminal Acts of Terrorism. None of these arrangements can be found in the current Indonesian criminal procedural law. The conclusion is that acts of terrorism have a significant impact on the community. They are not things, but rather frequent victims of Second Life. The preceding text makes it evident how many lives were lost in the blast. These fresh impacts originate from people's personal experiences. Acts of terrorism on a larger scale actually have an impact on many things, and that is a matter of life and death for people and the nation. This loss and threat can be explained from seven aspects/fields, namely defense and security, ideology, politics, economy, society, education, and religious relations. Related to article 43A regarding the prevention of Terrorism Crime, pre-emptive efforts are needed.

Average age upon decisions with truncated HARQ and optimization in the finite blocklength regime

We consider an update-and-decide IoT-based wireless network, where information packets generated from dual sources are co-stored in the transmitter’s buffer, while decisions are made at the destination. Two practical assumptions about the communications between the transmitter and destination are taken into account: the communications are operating with finite blocklength (FBL) codes, and truncated hybrid automatic repeat request (HARQ) schemes are exploited to improve the FBL reliability, i.e., the number of allowed rounds of (re)transmissions is finite. For the first time, this paper characterizes the timeliness of status updates, namely age upon decisions (AuD) (which highlights the timeliness of the information at decisions in comparison to the concept of age of information), for such truncated HARQ-assisted wireless network. First, we characterize the inter-arrival time between two adjacent successfully transmitted packets, while taking into consideration the preemption policy and the randomness of the number of preempted packets from the same source. In particular, the probability density function, statistical performance of such inter-arrival time are derived. Following these characterizations, we propose a new approach to determine the average AuD and obtain a closed-form expression accordingly. Subsequently, a joint blocklength and arrival rate optimization problem is considered to minimize the obtained average AuD. Before addressing the formulated problem, we prove the convexity of decoding error probability in CC-HARQ and IR-HARQ with respect to blocklength. Then, we prove the convexity of average AuD with respect to blocklength and arrival rate, respectively. By an efficient alternating algorithm, we obtain a efficient solution. Via simulations, we evaluate the performance and conclude a set of guidelines for designs on the considered network.

Analysis of the Effectiveness of Policy Guarantee Support under the COVID-19 Pandemic Economic Crisis

The purpose of this study is to suggest some policy implications by analyzing the support effectiveness of policy guarantees supported through the supplementary budget. During the COVID-19 period, the sales growth rate of the policy guarantee beneficiary companies was about 4.98% and the employment growth rate was about 0.46%, indicating a significant difference in growth potential compared to the non-beneficiary companies. First, among the economic crises caused by COVID-19, the crisis response through policy guarantees was relatively appropriate. Second, it is necessary to maintain an ‘appropriate’ level of support for ‘necessary’ economic sectors according to the government’s policy direction. Third, policy guarantee support can be effectively used as one of crisis response policies based on the effectiveness of the policy. Fourth, it is necessary to prepare for preemptive policy guarantee support by operating the crisis prediction system. Fifth, it is necessary to identify and prepare for possible crises after COVID-19 at the present time.

Impact of relaxing flood policy interventions on fish production: lessons from earthen pond-based farmers in Southwest Nigeria

These days, aquatic (fish) welfare is a major issue and a significant component that affects fish output. Although numerous factors can be involved, climate-induced floods are one of the most critical limiting factors in the aquaculture and fisheries industry’s development. Understanding the extent of losses and damages caused by floods at the farm level will thereby exacerbate pre-emptive policy responses. Thus, the impact of floods on fish production by focusing on catfish earthen pond-based farmers in Southwest Nigeria is presented. A survey is conducted for 150 fish farms in the region. A marginal treatment effects (MTE) approach is employed to determine the heterogeneity across the households and the policy-relevant treatment effects (PRTE). The results show significant heterogeneity in the effects of floods on fish production, considering both observed and unobserved characteristics of the farmers. It is shown that flood significantly increases output loss. Furthermore, farmers with high propensity scores to flood tend to have a high likelihood of incurring output loss. The estimates of PRTE reveal that relaxing policy strategies, such as access to climate information and climate-related training and workshops, would significantly exacerbate output loss due to flood incidences. Thus, intensifying awareness and sensitization on climate change policies will address the flood menace and still increase food production.

Short Packet-Based Status Updates in Cognitive Internet of Things: Analysis and Optimization

In the cellular Internet of Things (IoT), some machine type communication devices (MTCDs) are used to sample and send status information of monitored targets to help base station (BS) perform monitoring or controlling tasks. However, due to limited spectrum resources, the MTCDs often cannot occupy separate spectrum resources. This paper studies a cognitive IoT where the MTCDs exploit the spectrum resource vacated by cellular users to send status packets to the BS. The timeliness of status updates is characterized by the recently proposed metric, age of information (AoI). In the IoT, the packets sent by the MTCDs are often short, which means it is necessary to analyze the status updates under short packet communication theory (SPC). In this case, we adopt the automatic repeat request protocol to retransmit the erroneous packets, and the preemption policy is exploited to improve the status update performance. We first carefully analyze the evolution of AoI in the cognitive IoT, and adopt a recursive method to obtain the closed-form expression of the average peak AoI. Then, we analyze age-energy tradeoff, and propose a scheme of jointly optimizing transmit power, packet length, and spectrum sharing to reduce the average peak AoI of the network. The simulation results verify the correctness of the theoretical analysis, and show that the proposed scheme outperforms the benchmark schemes.

Policy learning and change during crisis: COVID-19 policy responses across six states.

Whereas policy change is often characterized as a gradual and incremental process, effective crisis response necessitates that organizations adapt to evolving problems in near real time. Nowhere is this dynamic more evident than in the case of COVID-19, which forced subnational governments to constantly adjust and recalibrate public health and disease mitigation measures in the face of changing patterns of viral transmission and the emergence of new information. This study assesses (a) the extent to which subnational policies changed over the course of the pandemic; (b) whether these changes are emblematic of policy learning; and (c) the drivers of these changes, namely changing political and public health conditions. Using a novel dataset analyzing each policy's content, including its timing of enactment, substantive focus, stringency, and similar variables, results indicate the pandemic response varied significantly across states. The states examined were responsive to both changing public health and political conditions. This study identifies patterns of preemptive policy learning, which denotes learning in anticipation of an emerging hazard. In doing so, the study provides important insights into the dynamics of policy learning and change during disaster.

Preemptive Policies and Risk-Off Shocks in Emerging Markets

Preemptive Policies and Risk-Off Shocks in Emerging Markets

Preemptive Policies and Risk-Off Shocks in Emerging Markets

Preemptive Policies and Risk-Off Shocks in Emerging Markets

430. Strategies for Prevention of COVID-19 Transmission in Hospitals

BackgroundInfection control measures against the coronavirus disease 2019 (COVID-19) within a hospital often rely on expert experience and intuition due to the lack of clear guidelines. This study surveyed current strategies for the prevention of the spread of COVID-19 in medical institutions.MethodsUpon systematic review of the guidelines at the national level, 14 key topics were selected. Six hospitals were provided an open survey that assessed their responses to these topics between August 11 and 25, 2020. Using these data, an online questionnaire was developed and sent to the infection control teams of 46 hospitals in South Korea. The survey was conducted between January 31, 2021, and February 20, 2021.ResultsAll 46 hospitals responded to the survey, and 24 hospitals (52.2%) had treated 100 or more cases of COVID-19. All hospitals operated screening clinics, and the criteria were respiratory symptoms (100%), fever (97.8%), and epidemiological association (93.5%). It was found that 89.1% (41/46) of hospitals allowed symptomatic patients to visit their general outpatient clinics if fever or respiratory symptoms were not associated with COVID-19. Most hospitals (87.2%; 34/39) conducted polymerase chain reaction (PCR) tests for all hospitalized patients. Moreover, 76.1% (35/46) of hospitals implemented preemptive isolation policies for hospitalized patients, of which 97.1% (34/35) were released from isolation after a single negative PCR test. A little over half of the hospitals (58.7%; 27/46) treated patients that met the national criteria for release from isolation but consistently had positive PCR results. Of these hospitals, 63% (17/27) used N95/KF94 masks, and 40.7% (11/27) used surgical masks without other personal protective equipment for treating them. Most hospitals (76.9%; 20/26) accommodated them in shared rooms when the cycle threshold value of the PCR test was more than a certain value (34.6%; 9/26), or after a certain period that satisfied the national criteria (26.9%; 7/26). Finally, 76.1% (35/46) of hospitals performed emergency procedures or operations on suspected patients.Table 1. Screening and selective treatment policy to prevent COVID-19 patients from entering the hospital NoteValues are presented as number (%) Abbreviations: COVID-19, coronavirus disease 2019; PCR, polymerase chain reaction 1 This question requested the respondent to select multiple items. 2 Suspected cases of COVID-19 include fever, respiratory symptoms, and epidemiological associations with COVID-19 patients. NoteValues are presented as number (%) Abbreviations: COVID-19, coronavirus disease 2019; PCR, polymerase chain reaction; PAPR, powered air-purifying respirator; Ct, cycle threshold 1 This question requested the respondent to select multiple items. 2 It includes infectious diseases, pulmonology, and the infection control and prevention office. 3 One hospital that wrote a non-categorical answer for the question was excluded. The hospital made a decision after discussing it with an infectious diseases specialist.ConclusionVarious guidelines were being applied by each medical institution, but there was a lack of an explicit set of national guidelines to support them.Disclosures All Authors: No reported disclosures

On the optimality of the earliest due date rule in stochastic scheduling and in queueing

We consider an environment with m servers in parallel and n jobs. The n jobs have i.i.d. exponentially distributed processing requirements. The servers operate at different speeds and preemptions are allowed. The jobs have random release times that are not known in advance, but whenever a job is released, its due date is fixed and becomes known to the scheduler. We first consider three stochastic scheduling problems with three due date related objective functions and consider variations of the Earliest Due Date (EDD) rule, including the preemptive policy that at any point in time assigns the job with the Earliest Due Date to the Fastest Server (EDD-FS). Our optimality results turn out to be examples of stochastic scheduling problems that have relatively simple priority rules that are optimal while their deterministic counterparts do not allow such simple priority rules to be optimal. We furthermore extend our results to include a priority queueing model with m exponential servers that operate at different speeds and preemptions being allowed. The jobs arrive according to an arbitrary renewal process, and we assume that the utilization factor of the system is less than 1. Upon a job’s release the time difference between its due date and release time is set by the draw of a random variable from a given distribution. At a job’s release time, its due date is then immediately fixed and known while its actual processing time only becomes known upon its service completion. We show that for this priority queueing model the preemptive EDD-FS rule also minimizes the limit of several due date related objective functions as the number of jobs converges to infinity.

The Delphic forward guidance puzzle in New Keynesian models

When the central bank has information that can help the private sector better predict the future, should it communicate such information to the public? In purely forward-looking New Keynesian models, such Delphic forward guidance unambiguously reduces ex ante welfare by increasing the variability of inflation and the output gap. We call this phenomenon the Delphic forward guidance puzzle. In more elaborate models with endogenous state variables, a combination of Delphic forward guidance and preemptive policy actions may improve welfare. However, full information revelation is generally not optimal and what information needs to be revealed is highly model-dependent.

MMAP/(PH,PH)/1 Queue with Priority Loss through Feedback

In this paper, we consider two single server queueing systems to which customers of two distinct priorities (P1 and P2) arrive according to a Marked Markovian arrival process (MMAP). They are served according to two distinct phase type distributions. The probability of a P1 customer to feedback is θ on completion of his service. The feedback (P1) customers, as well as P2 customers, join the low priority queue. Low priority (P2) customers are taken for service from the head of the line whenever the P1 queue is found to be empty at the service completion epoch. We assume a finite waiting space for P1 customers and infinite waiting space for P2 customers. Two models are discussed in this paper. In model I, we assume that the service of P2 customers is according to a non-preemptive service discipline and in model II, the P2 customers service follow a preemptive policy. No feedback is permitted to customers in the P2 line. In the steady state these two models are compared through numerical experiments which reveal their respective performance characteristics.

Leveraging Machine Perfusion to Ameliorate Geographic Disparities in Organ Allocation

Leveraging Machine Perfusion to Ameliorate Geographic Disparities in Organ Allocation

COVID-19 seropositivity among non-medical frontline office staff from two cities in Rajasthan, India.

Aims:The indigenously developed Indian Council of Medical Research (ICMR)-NIV COVID Kavach IgG enzyme linked immunosorbent assay (ELISA) has been recommended for seroprevalence among vulnerable populations in India, which provided essential services throughout the lockdown. The staff working in the High Court was one such group. We compared anti-SARS-CoV-2 IgG seropositivity among the staff of Jodhpur and Jaipur High Courts, Rajasthan, India.Methods:Asymptomatic judiciary staff of Jodhpur and Jaipur benches of High Courts were enrolled after informed written consent. A questionnaire was filled and 3–5 ml venous blood was collected from participants. The ICMR-NIV COVID Kavach IgG ELISA and EUROIMMUN IgG ELISA were used for detection of Anti-SARS-CoV-2 IgG antibodies.Results:A total of 63 samples (41 from Jodhpur and 22 from Jaipur) were collected between 28th July to 4th August 2020. The overall anti-SARS-CoV-2 IgG seroprevalence was found to be 6.35%. Seropositivity was higher among the staff from Jaipur (13.64%) as compared to Jodhpur (2.44%). The Kavach ELISA results were in complete agreement with EUROIMMUN ELISA. The infection control measures were deemed effective.Conclusion:Seroprevalence among the staff of Jodhpur High Court was found to be lower than Jaipur, reflecting higher susceptibility to COVID-19 in the former. Many offices worldwide are closed till mid 2020 but need to come up with pre-emptive policies eventually. This study may help to anticipate the possible challenges when other government/private offices start functioning. The infection control practices of one workplace may help formulate guidelines for other offices.

Preemptible queues with advance reservations: Strategic behavior and revenue management

Consider an M/G/1 queuing system that supports advance reservations. In this system, strategic customers must decide whether to reserve a server in advance (thereby gaining higher priority) or forgo reservations. Reserving a server in advance bears a cost. The provider can further impact the customers’ reservation decisions via implementation of one of several priority-based preemption policies: (i) one in which any customer is subject to service preemption by a higher priority customer (PR); (ii) one in which service preemption does not occur (NP); and (iii) a hybrid policy in which only customers without a priority reservation are subject to service preemption (HPR). In this work, we characterize the strategic behavior of customers, equilibrium outcomes, and provider’s revenue maximization under each of these policies. In all the cases, we prove that (i) the only possible type of Nash equilibria is a threshold one based on the customers’ priorities; and (ii) the system load impacts both the structure and number of Nash equilibria. We also prove that HPR is the only policy in which (i) an equilibrium where all customers make reservations may exist; and (ii) the second moment of service impacts the equilibria. Finally, we prove that for any system load and any service distribution, the HPR policy yields the highest maximum revenue, followed in turn by the PR policy and the NP policy. We further show that the relative difference in the performance of the HPR and PR policies is greatest at low system load and under low service variance.

Asymmetric Impacts of Inflation on the US Bond Rates and FED’s Pre-Emptive Policy

Abstract This study investigates the asymmetric impacts of changes in inflation rates on the US bond rates. This investigation is constructed on the Fisher Equation. To this end, the nonlinear ARDL model is applied. Empirical findings indicate that only the decreases (π− t ) in inflation rates affect bond rates. This asymmetric impact therefore shapes the FED’s monetary policy in terms of determining the bond rates at lower cost. When the inflation rate rises, the FED will know (in advance) that they do not need to increase the bond rates. This reminds us the FED’s former pre-emptive strike policy against inflation.