Discretionary Policy Research Articles

Evaluating health policies with subnational disparities: a text-mining analysis of the Urban Employee Basic Medical Insurance Scheme in China.

Subnational disparities in most health systems often defy 'one-size-fits-all' approach in policy implementation. When local authorities implement a national policy in a decentralized context, they behave as a strategic policy actor in specifying the central mandates, selecting appropriate tools and setting key implementation parameters. Local policy discretion leads to diverse policy mixes across regions, thus complicating evidence-based evaluations of policy impacts. When measuring complex policy reforms, mainstream policy evaluation methodologies have tended to adopt simplified policy proxies that often disguise distinct policy choices across localities, leaving the heterogeneous effects of the same generic policy largely unknown. Using the emerging 'text-as-data' methodology and drawing from subnational policy documents, this study developed a novel approach to policy measurement through analysing policy big data. We applied this approach to examine the impacts of China's Urban Employee Basic Medical Insurance (UEBMI) on individuals' out-of-pocket (OOP) spending. We found substantial disparities in policy choices across prefectures when categorizing the UEBMI policy framework into benefit-expansion and cost-containment reforms. Overall, the UEBMI policies lowered enrollees' OOP spending in prefectures that embraced both benefit-expansion and cost-containment reforms. In contrast, the policies produced ill effects on OOP spending of UEBMI enrollees and uninsured workers in prefectures that carried out only benefit-expansion or cost-containment reforms. The micro-level impacts of UEBMI enrolment on OOP spending were conditional on whether prefectural benefit-expansion and cost-containment reforms were undertaken in concert. Only in prefectures that promulgated both types of reforms did UEBMI enrolment reduce OOP spending. These findings contribute to a comprehensive text-mining measurement approach to locally diverse policy efforts and an integration of macro-level policy analysis and micro-level individual analysis. Contextualizing policy measurements would improve the methodological rigour of health policy evaluations. This paper concludes with implications for health policymakers in China and beyond.

Inclusive Growth and Climate Change Mitigation Programs and Policies in the ASEAN: Fiscal Implications

Abstract Addressing urgent global climate change and inequality issues has been a major challenge for the ten AMS (ASEAN Member countries) given the diversity and local agendas with divergent political, economic, and social objectives. While regional policy frameworks prioritise harmonisation and inter-regional integration outcomes over national inequality and climate change policy goals, governments typically address the latter through discretionary policy add-ons that lead to policy fragmentation and competing fiscal goals that interfere with intermediate development plans. To achieve the aspired inequality outcomes (Regional Framework and Action Plan, ASEAN Declaration, 2013) and the ratified global climate targets (Paris Treaty 2015) simultaneously, such policy outcomes and commitments to collaborative policy action will need to be aligned within an integrated policy framework at the regional or global level, and externalities of economic activity internalised into a sustainable and inclusive fiscal model. Focusing on policy design, integration and evaluation aspects, this paper tests the hypothesis that, given the urgency of these issues, the ASEAN governments devised corrective and preventive measures to systematically mitigate these externalities through intervention at the policy level and multilateral coordination at the regional and global levels to achieve pro-green and pro-equity policy outcomes with a net social surplus. Adopting a qualitative methodology, this study conducts a structured literature search and subsequent document analysis, using advanced text mining techniques to extract, contextualise and map policy-relevant themes by geopolitical scope, policy intent and outcomes. Literature evidence confirmed that the ASEAN Member States have recognised and acknowledged the urgency of climate change and inequality challenges, and that these governments intervene at the local policy level and also engage in multilateral discussions, which lack formal commitment and transparency. This study could not produce literature evidence of a systematic approach by these governments internalising mitigation mechanisms into the fiscal policy frameworks to achieve the aspired inclusive and sustainable outcomes - by design, rather than discretionary policy add-ons - and thus, the hypothesis was rejected. Keywords: Sustainable fiscal policy, inclusive growth, climate change mitigation, policy integration, multilateral intervention, document analysis.

Milton Friedman and the Road to Monetarism: A Review Essay

Milton Friedman and the Road to Monetarism: A Review Essay

Should faecal microbiota transplantation be used earlier in the treatment framework?

At present, faecal microbiota transplantation is not approved by the US Food and Drug Administration for any indication in the USA, but can be used to prevent recurrent Clostridioides difficile infection according to the policy of enforcement discretion. Use of faecal microbiota transplantation is currently reserved for patients with multiple recurrent C difficile, defined as three or more episodes in total. Considering the success of this treatment, high efficacy, and reasonable safety profile of faecal microbiota transplantation, should this therapy be offered at an earlier stage in the treatment framework? Faecal microbiota transplantation for first or second Clostridioides difficile infection (EarlyFMT): a randomised, double-blind, placebo-controlled trialIn patients with first or second C difficile infection, first-line faecal microbiota transplantation is highly effective and superior to the standard of care vancomycin alone in achieving sustained resolution from C difficile. Full-Text PDF

Model-Free Deep Recurrent Q-Network Reinforcement Learning for Quantum Circuit Architectures Design

Artificial intelligence (AI) technology leads to new insights into the manipulation of quantum systems in the Noisy Intermediate-Scale Quantum (NISQ) era. Classical agent-based artificial intelligence algorithms provide a framework for the design or control of quantum systems. Traditional reinforcement learning methods are designed for the Markov Decision Process (MDP) and, hence, have difficulty in dealing with partially observable or quantum observable decision processes. Due to the difficulty of building or inferring a model of a specified quantum system, a model-free-based control approach is more practical and feasible than its counterpart of a model-based approach. In this work, we apply a model-free deep recurrent Q-network (DRQN) reinforcement learning method for qubit-based quantum circuit architecture design problems. This paper is the first attempt to solve the quantum circuit design problem from the recurrent reinforcement learning algorithm, while using discrete policy. Simulation results suggest that our long short-term memory (LSTM)-based DRQN method is able to learn quantum circuits for entangled Bell–Greenberger–Horne–Zeilinger (Bell–GHZ) states. However, since we also observe unstable learning curves in experiments, suggesting that the DRQN could be a promising method for AI-based quantum circuit design application, more investigation on the stability issue would be required.

Non-parametric discretization for probabilistic labeled data

• Weakly supervised non-parametric discretization. • Probabilistic labels • Class-conditioned kernel density estimation. • Exact/closed calculation of the points involved in the discretization policy. • High relative performance in retaining discriminative information under noise. Probabilistic label learning is a challenging task that arises from recent real-world problems within the weakly supervised classification framework. In this task algorithms have to deal with datasets where each instance has associated a set of probabilities belonging to different class labels. In this paper, we propose a supervised univariate non-parametric discretization algorithm based on kernel density estimation that can deal with probabilistic labeled data. The algorithm takes advantage of the estimation of the class conditional densities to produce different sets of cut points according to different smoothing parameters of the kernel. Then, the best set of cut points is selected according to a given supervised classification performance measure. The computational complexity is O ( N log N ) , where N is the number of instances. The proposal is tested on simulated probabilistic labeled data, which allows assessing the behavior with different noise degrees. The results show that the algorithm outperforms other discretization algorithms and is robust to different degrees of uncertainty.

Determinan Manipulasi Akrual Dalam Pelaporan Keuangan Pemerintah Daerah

This study aims to determine the effects of government size, fiscal capacity, fiscal distress, and legislature size on accrual manipulation in local government financial reporting. The study was conducted on 23 local governments in Aceh with data analysis using multiple linear regressions. The data is extracted from audited financial reports of the local governments for the period 2016-2020. This study uses the Modified Jones Model to measure the manipulation of accruals. The results show that the government size and fiscal distress have a negative effect on accrual manipulation, legislature size has a positive effect on accrual manipulation, and fiscal capacity have no effect on accrual manipulation. These results indicate that the accrual manipulation in financial reporting can occur due to discretionary policies carried out by local government officials with the aim of making their financial performance look good.

A model-based hybrid soft actor-critic deep reinforcement learning algorithm for optimal ventilator settings

A ventilator is a device that mechanically assists in pumping air into the lungs, which is a life-saving supportive therapy in an intensive care unit (ICU). In clinical scenarios, each patient has unique physiological circumstances and specific respiratory diseases, thus requiring individualized ventilator settings. Long-term supervision by experienced clinicians is essential to perform the task of precisely adjusting ventilator parameters and making timely modifications. Moreover, a tiny clinical error can result in severe lung injury, induce multi-system organ dysfunction, and increase mortality. To reduce the workload of clinicians and prevent medical errors, machine learning (ML), or more specifically, reinforcement learning (RL) methods, have been developed to automatically adjust the ventilator’s parameters and select optimal strategies. However, the ventilator settings contain both continuous (e.g., frequency) and discrete parameters (e.g., ventilation mode), making it challenging for conventional RL-based approaches to handle such problems. Meanwhile, it is necessary to develop models with high data efficiency to overcome medical data insufficiency. In this paper, we propose a model-based hybrid soft actor-critic (MHSAC) algorithm that is developed based on the classic soft actor-critic (SAC) and model-based policy optimization (MBPO) framework. This algorithm can learn both continuous and discrete policies according to the current and predictive state of patient’s physiological information with high data efficiency. Results reveal that our proposed model significantly outperforms the baseline models, achieving superior efficiency and high accuracy in the OpenAI Gym simulation environment. Our proposed model is capable of resolving mixed action space problems, enhancing data efficiency, and accelerating convergence, which can generate practical optimal ventilator settings, minimize possible medical errors, and provide clinical decision support.

MONETARY STRATEGIES DURING AND AFTER THE GREAT RECESSION: ECB VS NBS

The last few decades of the world economic structure have been characterized by a trend of global convergence in the context of the exponential interconnectedness of initially divergent financial markets. With deeper trade and financial integration, nationally oriented monetary policy is confronted with serious obstacles and limitations, having in mind higher vulnerability to the external crisis shocks. The focus of this analysis is the heterogeneous monetary responses of the ECB and the NBS to the same external shocks induced by the Great 2008 Recession. The main findings suggest that both monetary systems should rely on discretionary policy taking current macroeconomic health into account. In contrast to the monetary responses to the Global Recession, the analysis shows that the reactions to the COVID-19 crisis remained faithful to unorthodox measures in ECB’s case but unrelated in NBS’s case.

La Spina, Encarnación. 2020. La vulnerabilidad de las personas refugiadas ante el reto de la integración. Cizur Menor: Aranzadi Thomson Reuters. 251 p.

Drawing on European and comparative jurisprudence and reports, this book review synthesises minimal legal standards and discretionary policies aiming to mitigate vulnerability and promote integration among asylum seekers, refugees and beneficiaries of international protection. It also highlights some of the gaps and inconsistencies that remain to be resolved for the Common European Asylum System to adequately protect the human rights of persons subjected to multiple, intersectional factors of vulnerability.

Subnational Social Investment in Three European Cities: An Exploratory Comparison

AbstractWith the evolution towards more service-intensive social investment welfare states across Europe, research on the institutional capacities of subnational welfare provision is increasingly relevant. Based on a comparative case analysis of three post-industrial municipalities in Europe, this article harbors a two-pronged objective: first, empirically, to show how regional and local governance capabilities are crucial to effective SI policy delivery; second, more positively, to bring out the proficiency of vertical coordination between national administration and subnational layers, alongside the critical role of horizontal policy discretion at the local level to align social benefits and capacitating services for the success of SI delivery; and, by implication, the overall responsiveness of national welfare systems to the changing nature of 21st century socioeconomic risks.

THE PROBLEM OF CORRUPTION LAW ENFORCEMENT THAT CAUSES STATE LOSSES SINCE THE CONSTITUTIONAL COURT OF THE REPUBLIC OF INDONESIA NUMBER 25 / PUU-XIV / 2016 DECISION

are increasingly widespread, so that the boundaries of the characteristics of acts of corruption and the characteristics of acts that are not corrupt but characterized by very detrimental to the state and society become difficult to distinguish, and lead to uncertainty about how to formulate groups. his crime. This research is a normative legal research that uses primary and secondary legal sources with library research collection techniques through legislation approach, historical approach and case approach. The results obtained are the legal considerations of the judges of the Constitutional Court of the Republic of Indonesia in the Decision of the Constitutional Court Number 25/PUU/XIV/2016 in Article 2 Paragraph (1) and Article 3 of Law Number 20 of 2001 concerning Eradication of Criminal Acts of Corruption in Decision Number 25/ PUU-XIV/2016 which grants the abolition of the phrase “can” is to create legal certainty for the State Civil Apparatus (ASN) regarding discretionary policies or decisions or the implementation of the Ermessen freies principle which is criminalized as a criminal act of corruption because it is detrimental to state finances.

The role of short-time work and discretionary policy measures in mitigating the effects of the COVID-19 crisis in Germany

In this paper, we investigate the impact of the COVID-19 pandemic on German household income in 2020 using a micro-level approach. We combine a microsimulation model with novel labour market transition techniques to simulate the COVID-19 shock on the German labour market. We find the consequences of the labour market shock to be highly regressive with a strong impact on the poorest households. However, this effect is nearly entirely offset by automatic stabilisers and discretionary policy measures. We explore the cushioning effect of these policies in detail, showing that short-time working schemes and especially the one-off payments for children are effective in cushioning the income loss of the poor.

Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique

We introduce a model of the diffusion of an epidemic with demographically heterogeneous agents interacting socially on a spatially structured network. Contagion-risk averse agents respond behaviorally to the diffusion of the infections by limiting their social interactions. Schools and workplaces also respond by allowing students and employees to attend and work remotely. The spatial structure induces local herd immunities along socio-demographic dimensions, which significantly affect the dynamics of infections. We study several non-pharmaceutical interventions; e.g., i) lockdown rules, which set thresholds on the spread of the infection for the closing and reopening of economic activities; ii) neighborhood lockdowns, leveraging granular (neighborhood-level) information to improve the effectiveness public health policies; iii) selective lockdowns, which restrict social interactions by location (in the network) and by the demographic characteristics of the agents. Substantiating a “Lucas critique” argument, we assess the cost of naive discretionary policies ignoring agents and firms’ behavioral responses.

Seeing like a Zone: Privately deputized sovereignty within Toronto’s Sanctuary City

Scholarship is split between seeing the Sanctuary City movement in a progressivist light of anti-border civil society movements, or, viewed as another iteration of citizenship controls. Critics point out how Sanctuary Cities, wherein municipalities provide services regardless of immigration status, do little to guarantee security for undocumented peoples who are at constant risk of deportation. Those who are optimistic about the movement’s emancipatory potential celebrate Sanctuary Cities’ ability to challenge the policing of migration. Why are the interpretations of Sanctuary City policies so polarized? I argue Sanctuary City literature suffers from trying to resolve the contradictions of state-based citizenship, devolving the challenge to the city, thus obscuring how state officials, business, and civil society actors can each possess local sovereignty control over urban space. My paper develops the metric of ‘private deputized sovereignty’ to trace how local policy discretion can implement or contest control over citizenship enforcement powers. I investigate how ‘private deputized sovereignty’ emerges from zoning technology inherent to urban spatial production. Conceptually, I introduce ‘seeing like a zone’ as a heuristic to challenge methodological nationalism and cityism which assume sovereignty resides with corporeal structures. In applying zoning analysis to Toronto’s Sanctuary City policy, the paper identifies economic and sanctuary zones where jurisdictional exceptions empowers local authorities, civil society, and/or private actors to either grant amnesty or exile migrants. Toronto being located within an immigrant federal state and being a global city offers a case for multiscalar analysis where migrants’ well-being and harm depends on the ‘privately deputized sovereign’s’ zoning choices in workplaces, healthcare, schools and the street.

Effectiveness and Safety of Fecal Microbiota Transplantation for Clostridioides Difficile Infection: Results From a 5344-Patient Cohort Study

Effectiveness and Safety of Fecal Microbiota Transplantation for Clostridioides Difficile Infection: Results From a 5344-Patient Cohort Study

Monetary Policy in a Model of Growth

<ns3:p>Empirical evidence suggests that recessions have long-run effects on the economy's productive capacity. Recent literature embeds endogenous growth mechanisms within business cycle models to account for these "scarring" effects. The optimal conduct of monetary policy in these settings, however, remains largely unexplored. This paper augments the standard sticky-price New Keynesian (NK) to allow for endogenous dynamics in aggregate productivity. The model has a representation similar to the two-equation NK model, with an additional condition linking productivity growth to current and expected future output gaps. Absent state contingency in the subsidies that correct the externalities associated with productivity growth, optimal monetary policy sets inflation above target whenever the subsidies fall short of the externalities. In the recovery from a spell at the ZLB, the optimal discretionary policy sets inflation temporarily above target, helping mitigate the long-run damage. Following a cost-push shock that creates inflationary pressure, the central bank tolerates a larger rise in inflation than in a model with exogenous productivity. The gains from commitment include the central bank's ability to make credible promises about future output gaps in a way that allows it to manipulate current productivity growth.</ns3:p>

Formation and implementation of the country’s budget under conditions of the global COVID-19 pandemic

Relevance of research topic. The global COVID-19 pandemic is forcing government regulators to adjust the priorities of the state budget and tax system. Under such conditions, it is particularly important to ensure the effectiveness of the system of formation and implementation of the country's budget which allows to create conditions for expanding fiscal space. Formulation of the problem. Restrictive measures in the fight against the global COVID-19 pandemic negatively affects the fiscal policy of the state. Taxpayers need support from the state which in turn affects the structure of revenue and expenditure budgets at all levels. To increase the level of socio-economic development of the country and territorial communities it is necessary to ensure balanced fiscal regulation. Analysis of recent research and publications. The issue of formation and implementation of the country's budget is widely reflected in the works of foreign and domestic scholars: J. Keynes, A. Laffer, R. Musgrave, P. Samuelson, J. Stiglitz, W. Tanzi, I. Adamenko, Y. Zhalilo, L. Lysiak, I. Lukianenko, V. Makohon, M. Pasichnyi, Yu. Radionov, I. Chuhunov and others. Selection of unexplored parts of the general problem. The growing fiscal risks caused by the destabilizing impact of the global COVID-19 pandemic require strengthening the soundness of the process of formation and implementation of the country's budget. Problem setting, research goals. The main objectives of the study are: to show the peculiarities of the formation and implementation of the country's budget in the global COVID-19 pandemic; to substantiate the main directions of improving the system of formation and implementation of the country's budget under modern conditions. The purpose of the study is to assess the peculiarities of the formation and implementation of the country's budget in the global COVID-19 pandemic. Research methodology. The article uses a set of methods and approaches: systemic and structural approach, statistical analysis, structuring, comparative approach, factorial approach, etc. Results of work. The essence and role of the fiscal system under the conditions of social and economic instability are revealed. The peculiarities of the formation and implementation of the national budget in the global COVID-19 pandemic are shown. The comparative analysis and assessment of the main budget and tax indicators in the countries with developed and transformational economies is carried out. The main directions of improving the system of formation and implementation of the country's budget under conditions of the global COVID-19 pandemic at all levels of the budget system are substantiated. Area of application of results. The results of the study can be used in the formation and implementation of fiscal policy under modern conditions. Conclusions. The crisis provoked by the global COVID-19 pandemic is negatively affecting the fiscal policy of the state, and therefore public authorities must take prudent and reasonable measures of discretionary fiscal policy, including during the formation and implementation of the state budget. Significant fiscal support measures taken by the government to combat COVID-19 are designed to support taxpayers by reducing tax pressures and increasing state social assistance, which is important to ensure economic growth and employment. Health policy, unemployment benefits, government support for corporate liquidity, remittances and wage subsidies increase the expenditure side of the budget. On the other hand, the difficult macroeconomic conditions caused by the global COVID-19 pandemic create and maintain significant budgetary risks while ensuring the proper level of revenue execution of budgets at all levels.

COVID-19 and (gender) inequality in income: the impact of discretionary policy measures in Austria

This paper analyzes the impact of the COVID-19 crisis on household income in Austria, using detailed administrative labor market data, in combination with micro-simulation techniques that enable specific labor market transitions to be modeled. We find that discretionary fiscal policy measures in Austria are key to counteracting the inequality- and poverty-enhancing effect of COVID-19. Additionally, we find that females tend to experience a greater loss in terms of market income. The Austrian tax–benefit system, however, reduces this gender differences. Disposable income has dropped by around 1% for both males and females. By comparison, males profit mainly from short-time work scheme, while females profit especially from other discretionary policy measures, such as the one-off payment for children.

Dynamic Pricing with Point Redemption

Problem definition: Reward points function as a new currency that consumers can spend on products and services. We study how point redemption affects the seller’s day-to-day pricing and inventory decisions. Academic/practical relevance: Despite widespread use of point redemption, little has been done on its implication on the seller’s operational decisions. This paper extends the revenue management literature to incorporate the impact of point redemption and provides managerial insights on how the seller can factor point redemption into decisions about price and inventory. Methodology: We develop a choice model in which a consumer chooses to pay with cash or points based on the attributes of reservation price, point balance, and the perceived value of a point. We incorporate this choice model into a dynamic model where a seller adjusts the price along with redemption availability and the required point amount. Results: We show that the effect of point redemption on the seller’s price is nontrivial, as the optimal price tilts upward or downward to the reimbursement rate (the compensatory revenue for a reward sale) depending on the inventory level, time, and the reimbursement rate. Furthermore, such price adjustments can attenuate the optimal markup/markdown level, reducing the price fluctuation derived by a dynamic pricing policy in the absence of reward sales. We find that operationalizing reward sales with some discretionary policies (e.g., control over the reward availability or point requirement) can considerably increase the seller’s revenue. Managerial implications: Our results guide how sellers manage prices and inventory dynamically when consumers can redeem points for purchases. Specifically, we show that a seller can benefit from allowing reward sales even when the reimbursement rate is substantially lower than the cash price. Although the seller benefits from having full control over the required point balance, the greatest benefit can be realized via the control of reward availability.