Hypothetical Policy Research Articles

Multicriteria-based decision aiding technique for assessing energy policy elements-demonstration to a case in Bangladesh

The adverse environmental consequences and diminishing trend of fossil fuel reserves indicate a serious need for vibrant and judicious energy policy. Energy policy involves a number of stakeholders, and needs to incorporate the interests and requirements of all the key stakeholder groups. This paper presents a methodological technique to assist with formulating, evaluating, and promoting the energy policy of a country in a transparent and representative way with clear scientific justifications and balanced assessments. The multicriteria decision analysis approach has been a widely used technique for evaluating different alternatives based on the interests of a multitude of stakeholders, and goals. This paper utilizes the SMAA (Stochastic Multicriteria Acceptability Analysis) tool, which can evaluate different alternatives by incorporating multiple criteria, in order to examine the preferences of different policy elements. We further extend this technique by incorporating the LEAP model (Long-range Energy Alternatives Planning system) to assess the emission impacts of different policy elements. We demonstrate the application of this evaluation technique by an analysis of four hypothetical policy elements namely Business-as usual (BAU), Renewables (REN), Renewable-biomass only (REN-b), and Energy conservation and efficient technologies (ECET). These are applied to the case of sharing fuel sources for power generation for the Bangladesh power sector. We found that the REN-b and REN policy elements were the best and second best alternatives with 41% and 32% acceptability respectively. This technique gives transparent information for choosing appropriate policy elements that aimed at sustainable energy.

Applying the Kuhn–Tucker model to estimate the value of recreational ecosystem services in Sicily

This paper applies the Kuhn–Tucker model to estimate recreation demand of parks in Sicily. We estimate a fixed coefficient specification and a random coefficient specification to take into account heterogeneity across visitors. Estimates suggest a diversity of preferences across the population and that parks with higher level of quality attributes are more likely to be visited. We also simulate two sets of hypothetical policy scenarios to evaluate and compare the recreational value of each park and the welfare impacts of changes in a quality attribute.

Choice in politics: Equivalency framing in economic policy decisions and the influence of expertise

Political decision-making involves the presentation of policy options from opposing points of view and in different lights. We test whether economic policy decisions are subject to equivalency framing by presenting survey participants with binary risky-choice decisions in hypothetical policy scenarios. Potentially mediating influences of expertise on the framing effect are explored using responses of students and professionals. Expertise is thereby defined in line with common education and work experience criteria in the recruitment of public officials. We mostly find unidirectional framing effects in the economic policy scenarios and a similar susceptibility of respondents with different levels of expertise. A logistic regression of the expertise variables on the choice between certain and risky options reveals only the frame to have a systematically significant effect across scenarios. The results indicate that expertise may not necessarily help to make better policy choices under risk, if the available options are framed differently.

When Do People Prefer Carrots to Sticks? A Robust 'Matching Effect' in Policy Evaluation

We find a “matching effect” in policy evaluations. For behaviors seen as positive but voluntary (such as organ donation) people prefer policies that are framed as advantaging those who act positively rather than disadvantaging those who fail to do so. Conversely, for behaviors seen as positive and obligatory, people prefer policies that are framed as disadvantaging those who fail to fulfill obligations rather than advantaging those who do so. We find that these differences in policy evaluations occur even when policy outcomes are identical, i.e., when the only difference between the policies is how they are framed. These differences emerge both for evaluations of hypothetical policies, as well as when implementation of the policy directly affects the evaluator. Furthermore, differences in evaluations are not the result of misunderstanding of — or lack of deliberation about — policy outcomes. Rather, the matching effect appears to follow from lay beliefs about when punishment is and is not appropriate.

The economics of space debris: Estimating the costs and benefits of debris mitigation

This paper models and quantifies the externalities from space debris. We develop an analytical model that includes debris collisional breakup and new generation of mission-related and fragmentation-related debris. We then derive empirically tractable formulas for several hypothetical policy interventions including (i) an optimized set of launch taxes, and various ex ante and ex post rebates, to promote debris mitigation; (ii) technology standards imposed under voluntary or mandatory regulatory approaches; and (iii) optimal penalties for debris generation that might be imposed ex post under a liability system. The formulas are implemented following an extensive estimation of parameter values compiled from debris generation models, engineering analyses of mitigation/adaptation technologies, productivity losses from collision risk, and spacecraft fleet projections. An analytical, empirically tractable model, with two time periods representing (in our case) time blocs up to and after 2030, and where variables are averaged over the time bloc provides considerable insight on the costs and benefits of space debris management in the near and medium term

Models and Insights for Hospital Inpatient Operations: Time-Dependent ED Boarding Time

One key factor contributing to emergency department (ED) overcrowding is prolonged waiting time for admission to inpatient wards, also known as ED boarding time. To gain insights into reducing this waiting time, we study operations in the inpatient wards and their interface with the ED. We focus on understanding the effect of inpatient discharge policies and other operational policies on the time-of-day waiting time performance, such as the fraction of patients waiting longer than six hours in the ED before being admitted. Based on an empirical study at a Singaporean hospital, we propose a novel stochastic processing network with the following characteristics to model inpatient operations: (1) A patient’s service time in the inpatient wards depends on that patient’s admission and discharge times and length of stay. The service times capture a two-time-scale phenomenon and are not independent and identically distributed. (2) Pre- and post-allocation delays model the extra amount of waiting caused by secondary bottlenecks other than bed unavailability, such as nurse shortage. (3) Patients waiting for a bed can overflow to a nonprimary ward when the waiting time reaches a threshold, where the threshold is time dependent. We show, via simulation studies, that our model is able to capture the inpatient flow dynamics at hourly resolution and can evaluate the impact of operational policies on both the daily and time-of-day waiting time performance. In particular, our model predicts that implementing a hypothetical policy can eliminate excessive waiting for those patients who request beds in mornings. This policy incorporates the following components: a discharge distribution with the first discharge peak between 8 a.m. and 9 a.m. and 26% of patients discharging before noon, and constant-mean allocation delays throughout the day. The insights gained from our model can help hospital managers to choose among different policies to implement depending on the choice of objective, such as to reduce the peak waiting in the morning or to reduce daily waiting time statistics. This paper was accepted by Assaf Zeevi, stochastic models and simulation.

Arms reduction and alternate Cold War histories

Alvin Saperstein recently reviewed Craig Nelson’s book The Age of Radiance: The Epic Rise and Dramatic Fall of the Atomic Era (Physics Today, September 2014, page 45). In that review, he asserted that “Ronald Reagan’s expensive drive for a high-tech defense against intercontinental ballistic missiles … considerably delayed the start of actual nuclear disarmament.” That assertion echoes Frank von Hippel’s idea of an alternative Cold War scenario with earlier US–Soviet arms-reduction agreements, which he spelled out in “Gorbachev’s unofficial arms-control advisers” (Physics Today, September 2013, page 41).I question how much confidence should be placed in historical analysis that is based on the possibility of changing a single input to a complex system—the timing of arms-reduction agreements—and expecting a corresponding change in output timing with no other major differences. The hypothetical policy alternative should instead be judged by its potential for having achieved a better outcome—if one can be envisioned—and should be weighed against the possibility of having produced a less favorable outcome. Those considerations were not addressed in von Hippel’s detailed discussion nor by Reagan policy critics whose writings appeared in earlier issues of Physics Today (see, for example, “The strategic offense initiative? The Soviets and Star Wars” by Peter Westwick, Physics Today, June 2008, page 43 and the item in Washington Reports, Physics Today, July 1988, page 47).For the Cold War, an extended struggle between two conflicting political-economic systems, the result of primary importance is the asymmetric outcome. That outcome, the collapse of the Soviet Union, brought immense benefits to one side: The US and its allies were intact, no longer threatened, and relieved of a huge and costly burden, and East European nations were freed from Soviet control and able to reestablish traditional ties with the West. Concerning arms reduction, the impending and actual Soviet collapse brought larger and more permanent reductions than any considered in prior negotiations.Likewise, negotiated arms reduction constituted only one facet of the multifaceted Cold War interactions. Those interactions included conflict and competition in political ideology, economic development, military power, science and technology, sports, culture, and global influence. They also included open and clandestine worldwide political action, along with covert human and technological penetration for espionage, sabotage, policy manipulation, and deception.I question the realism of assigning an exclusive and decisive role to arms-reduction agreements without considering the context created by the unceasing and contentious interactions that combined to produce the actual Cold War outcome and its long-lasting effects. Each suggested variant history constitutes an untested hypothesis. If the hypothesis is false, the variant outcome might have been comparably asymmetric in the reverse direction with a Soviet victory, or it might have been perfectly symmetric, in the form of mutual destruction.© 2015 American Institute of Physics.

Generational Accounting in Turkey

Generational Accounting, developed by Auerbach, Gokhale and Kotlikoff (1991), is an alternative and dynamic method employed in measuring the impact of existing fiscal policies on current and future generations. In contrast to the traditional and static measures of fiscal sustainability, the Generational Accounting method reveals the intergenerational distribution of tax burden and helps identify the policies that can alleviate the generational imbalance. This paper constructs and presents the first set of generational accounts for Turkey in an attempt to measure the generational gap and compare the Turkish intergenerational fiscal outlook with a number of developed and developing countries. Findings in the paper suggest that a 24.3% fiscal imbalance will be to the detriment of future generations in Turkey. Several hypothetical policy experiments have been implemented in the paper to correct the generational balance in Turkey.

What Do We Know About the Effectiveness of Leniency Policies? A Survey of the Empirical and Experimental Evidence

Over the last decade a large body of economic research has emerged that has sought to empirically test the effectiveness of leniency policies as tools to enhance the detection, prosecution and deterrence of cartel conduct. This research has considerable potential value in assisting competition authorities design optimal policies by having a better understanding of the impact that such policies, their specific features and manner of administration, have on the behaviour of cartel participants. Some researchers have taken the approach of testing empirically the effects of actual policies – predominantly those administered by the United States Department of Justice (USDOJ) and the European Commission (EC) – while others have tested different hypothetical policies in the lab. This section reviews the key studies which have been undertaken to date, it highlights the main findings and compares their results. After appreciating the main contributions and limitations of these studies, it concludes with a general assessment and an agenda for future research.

Using the SLEUTH Urban Growth Model to Simulate Future Urban Expansion of the Isfahan Metropolitan Area, Iran

Accelerating urban growth and land use/cover changes places increasingly pressure on the natural environment and human welfare and have become a global concern. Iran, as a developing country, is also experiencing growth of its urban areas during the last decades by high rate of rural–urban migration along with rapid socio-economic and political changes that has resulted in degrading environmental quality in many parts of Iran, particularly in the metropolitan areas such as Isfahan. Therefore, developing methods for assessing different urban growth planning scenarios and simulating urban expansion is critically important. The main goal of this study was simulating future urban expansion of Isfahan Metropolitan area from 2010 to 2050, by making use of cellular automata methodology in the SLEUTH modelling. The model was calibrated using historical data extracted from a time series of satellite images. The input data required by the model including Slope, Land use, Exclusion, Urban extent, Transportation and Hillshade were obtained from satellite images based on supervised classification. This research used the four images of Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) acquired 1976, 1990, 2001, and 2010. Two scenarios were planned to simulate the spatial pattern of urban growth. The first scenario was historical urban growth, which permitted urban development maintenance of the historical trend and the second scenario was a more compact growth as an answer to hypothetical policies and the lack of land to decrease urban spreading. Calibration of the SLEUTH model for Isfahan metropolitan area showed a high spread coefficient, which means that the predicted mode of growth in Isfahan is “organic” or edge growth. In Isfahan metropolitan area, topography was also shown to have an enormous effect in controlling the urban development. The results of this study invites many opportunities for further studies in many other regions which are experiencing growth of their urban areas and can be useful for planners, and policy makers to implement preventative or controlling factors in advance and make more informed strategic decisions.

The Limits of Inference with Theory: A Review of Wolpin (2013)

This essay reviews Kenneth I. Wolpin's (2013) monograph The Limits of Inference without Theory, which arose from lectures he presented at the Cowles Foundation in 2010 in honor of Tjalling Koopmans. While I readily agree with Wolpin's basic premise that empirical work that eschews the role of economic theory faces unnecessary self-imposed limits relative to empirical work that embraces and tries to test and improve economic theory, it is important to be aware that the use of economic theory is not a panacea. I point out that there are also serious limits to inference with theory: 1) there may be no truly “structural” (policy invariant) parameters, a key assumption underpinning the structural econometric approach that Wolpin and the Cowles Foundation have championed; 2) there is a curse of dimensionality that makes it very difficult for us to elucidate the detailed implications of economic theories, which is necessary to empirically implement and test these theories; 3) there is an identification problem that makes it impossible to decide between competing theories without imposing ad hoc auxiliary assumptions (such as parametric functional form assumptions); and 4) there is a problem of multiplicity and indeterminacy of equilibria that limits the predictive empirical content of many economic theories. I conclude that though these are very challenging problems, I agree with Wolpin and the Cowles Foundation that economists have far more to gain by trying to incorporate economic theory into empirical work and test and improve our theories than by rejecting theory and presuming that all interesting economic issues can be answered by well-designed controlled, randomized experiments and assuming that difficult questions of causality and evaluation of alternative hypothetical policies can be resolved by simply allowing the “data to speak for itself.” (JEL B41, C18)

Reform of the Barnett Formula with Needs Assessment: Can the Challenges be Overcome?

King D. and Eiser D. Reform of the Barnett Formula with needs assessment: can the challenges be overcome?, Regional Studies. Block grants to the UK's devolved administrations are allocated using the Barnett Formula. There have been calls to replace this formula with one based on spending needs assessment, but two obstacles to doing so have been raised. First, that the devolved administrations would be unable to agree on how needs should be assessed; and second, it is unclear how needs assessment might work for devolved governments that can pursue different spending policies. This paper investigates the first issue by analysing whether the Scottish and English formulae for allocating health and education funding within each country are statistically similar; and the second issue through a hypothetical policy simulation analysis.

A multi-agent model of a low income economy: simulating the distributional effects of natural disasters

This paper develops an agent-based model of a stylized low income region in order to study the impact of natural disasters on population displacement, income, prices, and consumption with a focus on distributions and coping strategies of low income groups. Key features of the model include the integration of decentralized markets into a full economy in a spatially explicit way and the analysis of short-run adjustment processes. The model is calibrated to a low income region of rural agrarian Pakistan that faced severe floods in 2010. Dynamic adaptation by agents in response to falling income includes migrating and running down savings. Despite these consumption smoothing strategies, some low income groups are vulnerable to starvation. The paper showcases two hypothetical policy scenarios, a cash and a food transfer program, and tracks their effects on the welfare of low income groups in the economy.

Policy Approaches Towards Undeclared Work: A Conceptual Framework

Policy Approaches Towards Undeclared Work: A Conceptual Framework

0351 G-estimation: why does it work and what does it offer?

ObjectivesStandard data analysis procedures provide biassed answers to etiologic questions in occupational studies. G-estimation is an alternative that allows researchers to avoid healthy worker survivor bias, and its results can...

Trade-offs between mobility and equity maximization under environmental capacity constraints: A case study of an integrated multi-objective model

This paper investigates the performance of a policy decision tool proposed for multi-objective decision under different policy interventions. This tool deals with the trade-off between mobility and equity maximization under environmental capacity constraints. Two system objectives, maximization of mobility and equity, are formulated in terms of the sum of total car ownership and number of trips, and the differences in accessibility between zones. Environmental capacities are based on production efficiency theory in which the frontier emission under maximum system efficiency is taken as environmental capacity. To examine the performance of the proposed model, three types of hypothetical policies (network improvement, population increase and urban sprawl) are formulated. Effects are simulated using data pertaining to Dalian City, China. Results show that the proposed model is capable of representing the trade-offs between mobility and equity based on different policy interventions. Compared with two extreme cases with the single objective of mobility maximization or equity maximization, the Pareto-optimal solutions provide more interesting practical options for decision makers. Taking the solution based on the maximum equity as an example, the policy of urban sprawl yields the most significant improvement in both emission and accessibility of the three scenarios.

Egalitarianism and altruism in health: some evidence of their relationship

BackgroundEgalitarianism and altruism are two ways in which people may have attitudes that go beyond the narrowly defined selfish preferences. The theoretical constructs of egalitarianism and altruism are different from each other, yet there may be connections between the two. This paper explores the empirical relationship between egalitarianism and altruism, in the context of health.MethodsWe define altruism as individual behaviour that aims to benefit another individual in need; and egalitarianism as a characteristic of a social welfare function, or a meta-level preference. Furthermore, we specify a model that explains the propensity of an individual to be egalitarian in terms of altruism and other background characteristics. Individuals who prefer a hypothetical policy that reduces socioeconomic inequalities in health outcomes over another that does not are regarded ‘egalitarian’ in the health domain. On the other hand, ‘altruism’ in the health context is captured by whether or not the same respondents are (or have been) regular blood donors, provided they are medically able to donate. Probit models are specified to estimate the relationship between egalitarianism and altruism, thus defined. A representative sample of the Spanish population was interviewed for the purpose (n = 417 valid cases).ResultsOverall, 75% of respondents are found to be egalitarians, whilst 35% are found to be altruists. We find that, once controlled for background characteristics, there is a statistically significant empirical relationship between egalitarianism and altruism in the health context. On average, the probability of an altruist individual supporting egalitarianism is 10% higher than for a non-altruist person. Regarding the other control variables, those living in high per capita income regions have a lower propensity and those who are politically left wing have a higher propensity to be an egalitarian. We do not find evidence of a relationship between egalitarianism and age, socioeconomic status or religious practices.ConclusionAltruist individuals have a higher probability to be egalitarians than would be expected from their observed background characteristics.

The impact of socioeconomic reforms on the work incentives in Latvia

Paper identifies the impact of the proposed and alternative socioeconomic reforms on changes in work incentives in Latvia. This paper aims at the assessing the role of Personal Income Tax and basic allowance in influencing Marginal Effective Tax Rates assessed using various scenarios of hypothetical policy changes. Results show that the tax reform implemented since 2014 has a relatively weak impact on the work incentives of Latvians.

Influence of Experience on Users’ Behaviour: A Day-to-Day Model for Route Choice Updating

The performance of a transportation network is the consequence of users’ choices and the interaction of these choices. Several aspects influence users’ choices. For the analyst of the transportation system, being able to forecast users’ behaviour is necessary in order to obtain a simulation close to the reality, and in order to predict the impact of hypothetical policy measures. In private car transport networks, the route choice of drivers is one of the key choice dimensions to be considered. We suppose that three main elements influence route choice: i) the subjective perception of travel times, ii) experience directly obtained on the network by the user, and iii) information acquired through information systems like Advanced Traveler Information Systems (ATIS). In particular, in the present paper we delve into the influence of information on choices, by exploring the influence of the process by which the perception of travel times is updated day-by-day due to experience obtained on the network. In our mathematical model, the users’ awareness/knowledge of actual conditions on the network changes through an evolution process. Although this kind of problem has been previously studied, a novel feature of our approach is that as a consequence of actual experience or information, users may become aware of new alternatives: hence the ‘choice set’ perceived to be available may change day-by-day, not only the perception of travel times within a given choice set. In this paper, therefore, the time-evolution of both the choice (the alternative actually chosen) and the choice set (the alternative considered) is investigated. An illustrative specification of the model is proposed, and a series of simulation experiments conducted.

Hepatitis B vaccination coverage rates among adults in rural China: Are economic barriers relevant?

BackgroundHepatitis B virus (HBV) infections cause major health problems in China. The Expanded Program of Immunization has succeeded in reducing infection rates among infants and children, but HBV vaccination coverage rates among adults remain low. ObjectiveThe objective was to investigate how individual adult HBV vaccination decisions are influenced by economic factors, socioeconomic status, and demographic characteristics, and to assess how potential vaccination policies could affect HBV vaccination coverage rates among adults. MethodsWe interviewed 22,618 adults, aged 15–59 years, from 7948 households, in 45 villages from 7 provinces. A questionnaire was used to collect information. The actual vaccine status was modeled using a polychotomous logistic regression with three outcomes; unvaccinated, partial vaccination, and complete vaccination. A subsample of unvaccinated adults gave responses to a hypothetical vaccination policy that offered HBV vaccination free of charge and various amounts of money to compensate for direct and indirect vaccination-related costs. ResultsThe polychotomous logistic regression results suggest that vaccination user fees, time needed to get a vaccination, and vaccination-related travel costs were negatively associated with HBV vaccination coverage rates. Higher income was associated with higher coverage rates, and coverage rates decrease with age, with no significant difference between the genders. In the subsample that responded to the hypothetical policy, 55–72% (depending on the amount of money offered as compensation) stated they would accept a vaccination if it was offered free of charge. ConclusionsOur polychotomous logistic regression results suggest that higher HBV vaccination coverage rates among adults are obtainable and that user fees, time needed to get a vaccination, and travel costs have acted as economic barriers to vaccination. This is supported by the responses to the hypothetical policy, which suggest that adult coverage rates could surge if HBV vaccine is offered at no cost.