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Title: Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem
Many cities struggle with financing their infrastructure projects. When decision makers cannot fully capture the benefits of their investments, there is a risk of underinvestment. Hong Kong’s transit operator created a model where it not only collects fare revenues but also engages in property management, leveraging the positive effects of public transport on nearby property values. In the article titled “Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem,” the authors present a stochastic Stackelberg game of timing to examine the reasoning behind this approach. The issue is complex because the operator faces a two-dimensional optimal stopping problem that cannot be simplified by changing the numéraire. The authors determine the operator’s optimal investment strategy through the use of a “penalized problem” and provide comparative statics. They also identify the conditions in which capitalizing on positive externalities can encourage infrastructure investment. Other management challenges share similar structures. more »« less
Akbarpour, Mohammad; Kominers, Scott Duke; Li, Kevin Michael; Li, Shengwu; Milgrom, Paul
(, Econometrica)
NA
(Ed.)
We study the investment incentives created by truthful mechanisms that allocate resources using approximation algorithms. Some approximation algorithms guarantee nearly 100% of the optimal welfare in the allocation problem but guarantee nothing when accounting for investment incentives. An algorithm's allocative and investment guarantees coincide if and only if itsconfirming negative externalitiesare sufficiently small. We introduce fast approximation algorithms for the knapsack problem that have no confirming negative externalities and guarantees close to 100% for both allocation and investment.
Abstract This paper develops the concept of flood problem framing to understand decision-makers’ priorities in flood risk management in the Los Angeles Metropolitan Region in California (LA Metro). Problem frames shape an individual’s preferences for particular management strategies and their future behaviors. While flooding is a complex, multifaceted problem, with multiple causes and multiple impacts, a decision-maker is most likely to manage only those dimensions of flooding about which they are aware or concerned. To evaluate flood decision-makers’ primary concerns related to flood exposure, vulnerability, and management in the LA Metro, we draw on focus groups with flood control districts, city planners, nonprofit organizations, and other flood-related decision-makers. We identify numerous concerns, including concerns about specific types of floods (e.g., fluvial vs pluvial) and impacts to diverse infrastructure and communities. Our analyses demonstrate that flood concerns aggregate into three problem frames: one concerned with large fluvial floods exacerbated by climate change and their housing, economic, and infrastructure impacts; one concerned with pluvial nuisance flooding, pollution, and historic underinvestment in communities; and one concerned with coastal and fluvial flooding’s ecosystem impacts. While each individual typically articulated concerns that overlapped with only one problem frame, each problem frame was discussed by numerous organization types, suggesting low barriers to cross-organizational coordination in flood planning and response. This paper also advances our understanding of flood risk perception in a region that does not face frequent large floods. Significance StatementThis paper investigates the primary concerns that planners, flood managers, and other decision-makers have about flooding in Southern California. This is important because the way that decision-makers understand flooding shapes the way that they will plan for and respond to flood events. We find that some decision-makers are primarily concerned with large floods affecting large swaths of infrastructure and housing; others are concerned with frequent, small floods that mobilize pollution in low-income areas; and others are concerned with protecting coastal ecosystems during sea level rise. Our results also highlight key priorities for research and practice, including the need for flexible and accessible flood data and education about how to evacuate.
A. Bensoussan, SingRu
(, Markov Processes And Related Fields)
To succeed in a competitive business environment, optimal capital investment plays a significant role. A firm cannot ignore the penalty associated with carrying excessive or insufficient production capacity. We provide a model of the optimal rate of capital investment under uncertainty incorporating a penalty to study the key impact. The penalty is modeled as a squared deviation between the expected and the desired levels. The payoff functional thus incorporates a nonlinear function of the expected capital level. This control problem is of the mean field type. We obtain a closed form solution by a direct method. As expected for mean field type control problems, the optimal feedback depends not only on the current states, but also on the initial conditions. We perform numerical studies to quantitatively address how risk control in capital level deviation affects the optimal investment policy.
Kody, Alyssa; Pianksy, Ryan; Molzahn; Daniel K
(, IREP Symposium on Bulk Power System Dynamics and Control-XI. A 100% Renewable Energy Source Bulk Power Grid: Opportunities and Challenges)
Wildfires pose a growing risk to public safety in regions like the western United States, and, historically, electric power systems have ignited some of the most destructive wildfires. To reduce wildfire ignition risks, power system operators preemptively de-energize high-risk power lines during extreme wildfire conditions as part of "Public Safety Power Shutoff" (PSPS) events. While capable of substantially reducing acute wildfire risks, PSPS events can also result in significant amounts of load shedding as the partially de-energized system may not be able to supply all customer demands. In this work, we investigate the extent to which infrastructure investments can support system operations during PSPS events by enabling reduced load shedding and wildfire ignition risk. We consider the installation of grid-scale batteries, solar PV, and line hardening or maintenance measures (e.g., undergrounding or increased vegetation management). Optimally selecting the locations, types, and sizes of these infrastructure investments requires considering the line de-energizations associated with PSPS events. Accordingly, this paper proposes a multi-period optimization formulation that locates and sizes infrastructure investments while simultaneously choosing line de-energizations to minimize wildfire ignition risk and load shedding. The proposed formulation is evaluated using two geolocated test cases along with realistic infrastructure investment parameters and actual wildfire risk data from the US Geological Survey. We evaluate the performance of investment choices by simulating de-energization decisions for the entire 2021 wildfire season with optimized infrastructure placements. With investment decisions varying significantly for different test cases, budgets, and operator priorities, the numerical results demonstrate the proposed formulation's value in tailoring investment choices to different settings.
Bensoussan, Alain; Cheung, Ka Chun; Li, Yiqun; Yam, Sheung Chi Phillip
(, Mathematical Finance)
Abstract Traditionally, mutual funds are mostly managed via an ad hoc approach, namely a terminal‐only optimization. Due to the intricate mathematical complexity of a continuum of constraints imposed, effects of the inter‐temporal reward for the managers are essentially neglected in the previous literature. For instance, the inter‐temporal optimal investment problem from the fund manager's viewpoint, who earns proportional management fees continuously (a golden rule in practice), has been outstanding for long. This article completely resolves this challenging question especially under generic running and terminal utilities, via the Dynamic Programming Principle which leads to a nonconventional, highly nonlinear HJB equation. We develop an original mathematical analysis to establish the unique existence of the classical solution of the primal problem. Further numerical calibrations and simulations for both the portfolio weight and the value functions illustrate the robustness of the optimal portfolio towards the manager's risk attitude, which allows different managers with various risk characteristics to sell essentially the same investment vehicle. Simulation studies also indicate that the policy of charging a substantial terminal‐only management fee can be replaced by another one with only a negligible amount over the interim period, which substantially reduces the total management fee paid by the clients without lowering the manager's satisfaction at all; this last observation echoes the magic of the alchemy of finance.
Bai, Hao, Bensoussan, Alain, Briest, Gordon, and Chevalier-Roignant, Benoît.
"Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem". Operations Research 73 (2). Country unknown/Code not available: Informs. https://doi.org/10.1287/opre.2023.0075.https://par.nsf.gov/biblio/10628561.
@article{osti_10628561,
place = {Country unknown/Code not available},
title = {Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem},
url = {https://par.nsf.gov/biblio/10628561},
DOI = {10.1287/opre.2023.0075},
abstractNote = {Many cities struggle with financing their infrastructure projects. When decision makers cannot fully capture the benefits of their investments, there is a risk of underinvestment. Hong Kong’s transit operator created a model where it not only collects fare revenues but also engages in property management, leveraging the positive effects of public transport on nearby property values. In the article titled “Monetizing Positive Externalities to Mitigate the Infrastructure Underinvestment Problem,” the authors present a stochastic Stackelberg game of timing to examine the reasoning behind this approach. The issue is complex because the operator faces a two-dimensional optimal stopping problem that cannot be simplified by changing the numéraire. The authors determine the operator’s optimal investment strategy through the use of a “penalized problem” and provide comparative statics. They also identify the conditions in which capitalizing on positive externalities can encourage infrastructure investment. Other management challenges share similar structures.},
journal = {Operations Research},
volume = {73},
number = {2},
publisher = {Informs},
author = {Bai, Hao and Bensoussan, Alain and Briest, Gordon and Chevalier-Roignant, Benoît},
}
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