Effects Of Different Policies Research Articles

An agent-based approach to study the diffusion rate and the effect of policies on joint placement of photovoltaic panels and green roof under climate change uncertainty

As two of the highest trending green technologies, photovoltaic panels and green roofs are proven to be effective practices for energy generation and energy saving. The achievable impact from the widespread installation of such technologies is, however, not clearly established. This is mainly because the degree of this impact highly depends on the inherently uncertain environmental and climate factors, as well as the unknown adoption rates of these technologies, which in turn depend on different characteristics of decision makers and interactions among them. To that end, this study aims to investigate the diffusion rate of these green technologies under uncertainties caused by climate change, characteristics of adopters, and their interactions. An integrated framework is developed to capture the interplay between financial and attitudinal aspects, as well as the uncertainties due to both the stochastic nature of system parameters and the interactions among agents involving human beings. Specifically, this framework consists of a integer programming model to optimize the green roof and/or photovoltaic panel installation settings for a given building under climate change uncertainty, and an agent-based model to factor in the role of human behavior and interactions. A case study for the city of Knoxville, TN, is presented to evaluate the effects of different policies on the diffusion rate of the green technologies of interest. The results show that the affordability of green technologies and public awareness are the key drivers of the adoption of these technologies, which highlight the important role of the decision makers in impacting the diffusion rate.

Can energy supply-side and demand-side policies for energy saving and emission reduction be synergistic?--- A simulated study on China's coal capacity cut and carbon tax

Existing literature mainly focuses on the combined effect of different policies on energy, economy and environment. However, most of them were based on the perspective of energy demand-side. In order to fill this gap, we study the effect of carbon tax and coal capacity cut from both the energy demand-side and energy supply-side using a dynamic Computable General Equilibrium (CGE) model. Different policy effects including single one and synergistic one are compared. Moreover, the synergy degrees of coal capacity cut and carbon tax in energy saving, emission reduction and economic growth are evaluated. The results show that both coal capacity cut and carbon tax are beneficial to energy conservation and carbon emission mitigation at the expense of a slight loss in economy. Mixed policy has better performance than single policy in carbon emission reduction and energy saving. Also, a more stringent policy is conducive to carbon emission mitigation and energy conservation. Additionally, there are significant synergistic effect of coal capacity cut and carbon tax from the perspectives of energy saving, emission reduction and economic growth. Therefore, the mixed policy of coal capacity cut and carbon tax should be promoted and an appropriate stringency level of policy mix should be adopted.

Insider-Outsider Labor Markets, Hysteresis and Monetary Policy

I develop a version of the New Keynesian model with insider-outsider labor markets and hysteresis that can account for the high persistence of European unemployment. I study the implications of that environment for the design of monetary policy. The optimal policy calls for strong emphasis on (un)employment stabilization which a standard interest rate rule fails to deliver, with the gap between the two increasing in the degree of hysteresis. Two simple targetiing rules are shown to approximate well the optimal policy. The properties of the model and effects of different policies are analyzed through the lens of the labor wedge and its components. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Evidence, rationality, and ignorance: Agnotological issues in COVID-19 science.

Two decades ago, Robert Proctor coined the term agnotology to refer to the study of ignorance that stems from scientific research. Amid the coronavirus disease pandemic, the world is witnessing the greatest natural experiment ever, and countries have adopted different response strategies. An evaluation of the effectiveness of different policies will play a valuable role in preparing for future public health emergencies. However, controversial issues such as the timing and pathways of viral emergence, the effectiveness of social distancing and lockdown strategies, and the use of antimalarial drugs as therapy have still not been fully resolved. This serves as a fertile breeding ground for agnotological strategies, whereby scientific studies are deliberately or unintentionally designed to create distractions or draw conclusions that are not supported by research findings. Researchers, public health authorities, and healthcare workers should be equipped to identify such agnotological strategies, distinguish them from scientific fraud, and avoid drawing misleading inferences based on an irrational adherence to hypotheses and a lack of criticism of implausible results.

Simulating Uneven Urban Spatial Expansion under Various Land Protection Strategies: Case Study on Southern Jiangsu Urban Agglomeration

Urban spatial expansion (USE) is an uneven process affected by both natural and human factors, and land use regulation policy is of significance. To indicate the potential effects of different policies at a regional scale and then improving them under the context of increasing emphasis on land protection, we take Southern Jiangsu Urban Agglomeration (SJUA) in eastern China as a case study. Based on USE simulation with a minimum cumulative resistance (MCR) model under four scenarios related with arable and ecological land protection, we analyze the spatial differentiation of newly added urban construction lands and examine the changes of urban system with fractal analysis. Results indicate the allocations of newly added urban construction land differs by scenarios as well as total expanding amounts, and larger cities tend to grow faster. The share of the four largest cities (Suzhou, Nanjing(S), Wuxi, and Changzhou) were mostly higher than 40%. Accordingly, the final area of all cities was linearly corrected with their extant sizes in 2010. However, the differentiated allocations of newly added urban lands related to both increasing expanding amounts and different scenarios caused differences in the said linear relationships and also influenced urban rank-size in different degrees. It is concluded that the MCR model is feasible for simulating regional scale urban expansion and land protection strategies do not induce dramatic changes to the basic structures of regional urban system, but they are slightly different as land protection strategies change. The spatial distribution of protected lands affect the differentiation of both the predicted expanding amount of different cities and the regional urban systems significantly. It is of importance to optimize the spatial distribution of protected lands to regulate regional scale USE patterns and also urban systems properly.

Investment decision on shallow geothermal heating & cooling based on compound options model: A case study of China

Developing shallow geothermal energy is expected to play an important role to supply affordable, clean and reliable heating by many countries in the world. However, the development is mainly hindered by the high upfront investment costs and various risks involved in the exploration, construction and operation phases. The present study proposed a compound options model to explore the optimal investment timing and value based on the consideration of both investment and operational flexibilities. The Least Square Monte Carlo and Markov Chain Monte Carlo methods were employed in the model to find the solutions. A case study was carried out for China, and five scenarios were simulated to understand the effects of different policies including subsidy, carbon trading mechanism, preferential taxation and preferential electricity price. The obtained results show that, (i) the incentive policies are essential for the development of shallow geothermal energy, which can attract more investment before 2030; (ii) the government is suggested to carry out a preferential electricity price for shallow geothermal development, rather than increase the subsidy; (iii) the application of compound options method increases the investment value in all five scenarios, but its impact on investment timing varies.

Carpooling with heterogeneous users in the bottleneck model

We investigate the effects of carpooling in a dynamic equilibrium model of congestion, which captures various dimensions of heterogeneity: heterogeneity in the preference for and cost of carpooling, heterogeneity in values of time and values of schedule delay. We investigate various policy scenarios: no-toll, first-best pricing, and subsidization of carpooling. The optimally differentiated subsidy equals each type of users’ marginal external benefit (MEB) of switching to m-person carpooling or carpooling, which turns out to be heterogeneous for “ratio heterogeneity”, where the ratios of the values of time and schedule delay vary, and homogeneous for “proportional heterogeneity”, where these values vary in fixed proportion over the population. If such differentiation over users is impossible, the subsidy is a weighted average of the MEB’s, with the weights reflecting the relative sensitivity of the group size of carpoolers to the subsidy. Using a numerical example, we investigate the welfare effects and distributional effects of different policies. The relative efficiency of the differentiated subsidization first increases and then falls with the degree of ratio heterogeneity, and decreases over the entire parameter range and more with the degree of proportional heterogeneity.

Bias in cohort-based comparisons of immigrants\u2019 health outcomes between countries: a simulation study

BackgroundCohort-type data are increasingly used to compare health outcomes of immigrants between countries, e.g. to assess the effects of different national integration policies. In such international comparisons, small differences in cardiovascular diseases risk or mortality rates have been interpreted as showing effects of different policies. We conjecture that cohort-type data sets available for such comparisons might not provide unbiased relative risk estimates between countries because of differentials in migration patterns occurring before the cohorts are being observed.MethodTwo simulation studies were performed to assess whether comparisons are biased if there are differences in 1. the way migrants arrived in the host countries, i.e. in a wave or continuously; 2. the effects on health of exposure to the host country; or 3., patterns of return-migration before a cohort is recruited. In the first simulation cardiovascular disease was the outcome and immortality in the second. Bias was evaluated using a Cox regression model adjusted for age and other dependant variables.ResultsComparing populations from wave vs. continuous migration may lead to bias only if the duration of stay has a dose-response effect (increase in simulated cardiovascular disease risk by 5% every 5 years vs. no risk: hazard-ratio 1.20(0.15); by 10% every 5 years: 1.47(0.14)). Differentials in return-migration patterns lead to bias in mortality rate ratios (MRR). The direction (under- or overestimation) and size of the bias depends on the model (MRR from 0.92(0.01) to 1.09(0.01)).ConclusionThe order of magnitude of the effects interpreted as due to integration policies in the literature is the same as the bias in our simulations. Future studies need to take into account duration and relevance of exposure and return-migration to make valid inferences about the effects of integration policies on the health of immigrants.

Integrated decision-making framework for urban freight logistics policy-making

The urban freight logistics policy-making process takes place in a complex environment and presents numerous challenges, such as difficult trade-offs between the objectives of various stakeholders, unclear problem ownership, and a lack of data on and awareness of urban freight issues. Furthermore, the complex interactions and power dynamics between different stakeholders introduce additional difficulties when attempting to predict the effects of different policies. In this study, we extend the current perspective on urban logistics decision-making by adopting a Complex Adaptive System (CAS) perspective. This allows us to better interpret the behaviors of urban logistics stakeholders and elucidate some of the most pressing challenges encountered in urban logistics policy-making. Building on the extant urban logistics and CAS literature, we establish an integrative decision-making framework that aims at increasing the success of urban logistics policies. Finally, we apply our framework to a case study in order to illustrate the operationalization of the proposed CAS perspective in an empirical setting on urban logistics policy-making.

Modeling the effects of urban expansion on regional carbon storage by coupling SLEUTH‐3r model and InVEST model

AbstractModeling the impacts of urbanization on carbon storage has become a critical and hot topic in the fields of mitigating global warming. This study coupled urban expansion and land use change simulation and prediction model (SLEUTH‐3r model) and ecosystem service evaluation model (InVEST model) to analyze and predict the impacts of urbanization on carbon storage in Shizuishan, a city located in the northwestern of China. Scenarios analysis was used to compare the effects of different policies on carbon storage, while the policies concern about urban growth pattern, ecological protection and socioeconomic development. The results suggested that (1) the coupled model can predict carbon storage change with urbanization in a high accuracy (relative error within ±5% for 94.6% of the whole area); (2) carbon storage of Shizuishan experienced a loss of 2.70 Tg in 1989–2015, and would continue to experience a loss of 6.18 Tg, 5.27 Tg, 3.76 Tg and 2.47 Tg under historical growth scenario (HGS), decrease socioeconomic scenario (DSS), compact growth scenario (CGS) and ecological protection scenario (EPS) in 2015–2035, respectively; (3) compact urban growth pattern and ecological protection policy can both decrease the negative effects of urbanization on carbon storage. Multiple ecosystem services should be integrated into urban planning to achieve a balance of socioeconomic development and environment protection.

Deconstructing the policyscape for reducing deforestation in the Eastern Amazon: Practical insights for a landscape approach

AbstractIn international debates on climate change mitigation and forests, there is increased recognition of the importance of a landscape approach to effectively address tropical deforestation. Such an approach, although increasingly promoted, remains only loosely defined and requires further development in order to effectively integrate different interventions at landscape level. In particular, it is important to understand the possible interactions between different landscape interventions at local level—where they are intended to have effect—and the challenges associated with them. Inspired by the complexity of policy mix analysis, this article seeks to shed light on these interactions by analysing how different policies and measures for reducing deforestation and degradation have played out in a jurisdiction with wide‐ranging actors and interventions aimed at shaping their behaviour. Focusing on smallholders, we examine the Sustainable Landscapes Pilot Programme in São Félix do Xingu, looking at how different policies interact—categorising interactions as “complementary,” “mutually reinforcing” (synergistic), “in conflict,” “interdependent,” and/or “redundant”—and explain how proponents of this pilot programme seek to integrate them. Most analysis is based on primary data collected through quantitative (i.e., random stratified sampling and surveys) and qualitative (i.e., observation and focus groups) methods. The São Félix do Xingu case shows that understanding effects of different policies and measures on people's behaviour requires a deeper look at local perceptions and reactions to such policies and measures, something most studies on the topic have overlooked. Ultimately, the heterogeneity and complexity of social practices that permeate landscapes must be recognised in order to integrate diverse measures to reduce deforestation.

Integrated sustainability assessment of chemical production chains

The chlor-alkali/polyvinyl chloride production chain is characterized by high levels of energy consumption and emissions. The sustainable development of this industry has become a growing concern in the face of finite resources and the increasing demand. In the production chain, environmental, energy, and economic aspects are intricately linked. Thus, it's important to investigate how this industry can develop sustainably by examining the interactions among these three aspects. This paper evaluates the chlor-alkali/polyvinyl chloride production chain by using an integrated method combining the driving force-pressure-state-impact-response framework and system dynamics. First, the driving force-pressure-state-impact-response framework is used to investigate the interactions between society and the environment in the development of the production chain. Selected indicators were defined to characterize each subsystem in order to evaluate these interactions quantitatively. Next, system dynamics models are developed to explore the interactions among the three subsystems via causality loops. Five scenarios of the development of chlor-alkali/polyvinyl chloride production chain were simulated to see the effect of different policies on the subsystems. The results show that the sustainable development scenario showed reductions of 52% in energy intensity and 88% in chemical oxygen demand load intensity compared to business as usual. This integrated methodology can also be used as a decision-support tool for the design, planning, and management of the production chains of other process industries.

On the Effectiveness of Loan-to-Value Regulation in a Multiconstraint Framework

Models in the infinite horizon macro-housing literature often assume that borrowers are constrained exclusively by the loan-to-value (LTV) ratio. Motivated by the Swedish micro-data, I explore an alternative arrangement where borrowers are constrained by the feasibility of repayment, but choose a house of maximum permissible size conditional on the LTV restriction. While stricter LTV limits are often considered as a measure to tackle the rise in household indebtedness, I find that policy designed to lower the maximum permissible LTV ratio may actually leave the debt-to-GDP ratio unchanged and increase housing prices in equilibrium if borrowers are bound by two constraints at the same time. In a model with occasionally binding constraints, I show that also for the analysis of the short-run effects of different policies, the consideration of multiple constraints, possibly binding at the same time, is important. The effectiveness of LTV as a measure to tackle the rise in indebtedness has to be reassessed and is likely lower than previously shown.

Assessment of urban passenger fleet emissions to quantify climate and air quality co-benefits resulting from potential interventions

Lack of robust data to assess the effects of different policies may hamper the design and implementation of effective solutions to reduce traffic emissions. This study analyzed the emissions of passenger fleets in Bandung, Indonesia, illustrated with three emission scenarios against the 2015 baseline. Local surveys were conducted to get traffic activity data for International Vehicle Emissions (IVE) modeling to generate emission factors (EFs) relevant to actual fleets and driving conditions in the city. EFs obtained for gasoline fleets that could have been affected by the leaded gasoline used prior 2006 were adjusted for the catalyst deactivation effect. Annual emissions (Gg/year) for CO, VOC, NOx, PM, BC, OC, NH3, air toxics and SO2 were 168, 36, 16, 1.8, 0.68, 0.72, 0.68, 4.7 and 0.42, respectively. Emissions of CO2, N2O and CH4 were 2679; 0.07 and 5.8 Gg/year, respectively. Collectively, the 20-year global warming potential (GWP) of the emissions was 6770 Gg/year CO2 eq. Analysis of potential interventions of technology intrusion of Euro3 (S1) and Euro4 (S2), and catalyst revamping (S3) showed potential co-benefits to air quality improvement and climate forcing mitigation. S1 would reduce the toxic pollutants emissions by 62% and GWP by 29%; corresponding reductions would be 68% and 45% for S2 and 47% and 16% for S3. Actual measurements are required to validate the potential emission reductions by catalyst revamping.

Model for Evaluating CO2 Emissions and the Projection of the Transport Sector

This article presents a system dynamics model to analyze the growth of cars and the effect of different policies on carbon emissions from the transport sector. The simulation model used in this work was built using the methodology of systems dynamics (SD) developed by Jay W. Forrester at the Massachusetts Institute of Technology (MIT). The model was applied to the transport sector of the city of Bogota, Colombia for a period of time between 2005 and 2050. The information used to feed the model comes from reliable sources such as DANE (National Administrative Department of Statistics) and EIA (U.S Energy Information Administration). Four scenarios were proposed that relate urban development policy and environmental policy. The main results indicate that the number of cars in Bogota can reach up to 13 million vehicles in 2050 and the projection of CO2 emissions would reach 34 million TonCO2 in the absence of an appropriate environmental policy.

Capital Accumulation, Asset Price Dynamics and the Macroeconomy

This article develops a dependent economy model of determination of employment and asset prices that integrates the roles of relative prices, expectations and dynamics of capital accumulation. In this model, money wage is rigid which leads to persistence of unemployment. Labour and capital are used as factors of production in the traded sector while the non-traded sector uses labour and imported intermediate inputs. The article examines macroeconomic implications of selective economic reforms for asset price dynamics, growth and employment. The discussion of comparative static exercises shows that not only the effects of different policies are ambiguous but also the short-run and the long-run effects are qualitatively different. For example, tariff liberalization causes the short-run expansions of both traded and non-traded sectors but overtime it may depress the capital stock leading to contraction of both the sectors and an increase in unemployment. The broad message of this article is that the design of macroeconomic policy should not be purely based on considerations of the short-run effects of policy changes. JEL: E22, F13, F41

Discussion

Discussion

What gets measured gets managed: A new method of measuring household food waste

The quantification of household food waste is an essential part of setting policies and waste reduction goals, but it is very difficult to estimate. Current methods include either direct measurements (physical waste surveys) or measurements based on self-reports (diaries, interviews, and questionnaires). The main limitation of the first method is that it cannot always trace the waste source, i.e., an individual household, whereas the second method lacks objectivity. This article presents a new measurement method that offers a solution to these challenges by measuring daily produced food waste at the household level. This method is based on four main principles: (1) capturing waste as it enters the stream, (2) collecting waste samples at the doorstep, (3) using the individual household as the sampling unit, and (4) collecting and sorting waste daily. We tested the feasibility of the new method with an empirical study of 192 households, measuring the actual amounts of food waste from households as well as its composition. Household food waste accounted for 45% of total waste (573 g/day per capita), of which 54% was identified as avoidable. Approximately two thirds of avoidable waste consisted of vegetables and fruit. These results are similar to previous findings from waste surveys, yet the new method showed a higher level of accuracy. The feasibility test suggests that the proposed method provides a practical tool for policy makers for setting policy based on reliable empirical data and monitoring the effectiveness of different policies over time.

The Impact of Implementing Tobacco Control Policies: The 2017 Tobacco Control Policy Scorecard.

The Tobacco Control Scorecard, published in 2004, presented estimates of the effectiveness of different policies on smoking rates. Since its publication, new evidence has emerged. We update the Scorecard to include recent studies of demand-reducing tobacco policies for high-income countries. We include cigarette taxes, smoke-free air laws, media campaigns, comprehensive tobacco control programs, marketing bans, health warnings, and cessation treatment policies. To update the 2004 Scorecard, a narrative review was conducted on reviews and studies published after 2000, with additional focus on 3 policies in which previous evidence was limited: tobacco control programs, graphic health warnings, and marketing bans. We consider evaluation studies that measured the effects of policies on smoking behaviors. Based on these findings, we derive estimates of short-term and long-term policy effect sizes. Cigarette taxes, smoke-free air laws, marketing restrictions, and comprehensive tobacco control programs are each found to play important roles in reducing smoking prevalence. Cessation treatment policies and graphic health warnings also reduce smoking and, when combined with policies that increase quit attempts, can improve quit success. The effect sizes are broadly consistent with those previously reported for the 2004 Scorecard but now reflect the larger evidence base evaluating the impact of health warnings and advertising restrictions.

Impact of policy implementation on telecommunication diffusion in India

Telecommunication sector has emerged as a key driver of economic and social development. The thrust to ensure access of telecom services to a common man is a challenging task in a country like India where majority of the population reside in villages. The conducive policy can attract investments in this sector apart from generating manifold employment opportunities in the telecom sector. India is one of the fastest growing telecom markets in the world. The unprecedented increase in tele-density and sharp decline in tariffs in the telecom sector have contributed significantly to the country's economic growth. Besides contributing considerably to India's GDP, telecommunications along with information technology, has accelerated the growth of economic and social sectors. The objective of the study is to analyse effect of different policies on the telecommunication diffusion, hence, seven different policies of the telecom sector are analysed to study their impact on growth of telecom sector.