Researching the market and building a demand model

1998 ◽  
Author(s):  
null
Keyword(s):  
Demand Model

Solar Renewable Energy Credit Price Volatility and Investment Returns: Have Policies Stranded Capital Investment?

Commonwealth ◽  
2017 ◽  
Vol 19 (1) ◽  
Author(s):  
Somayeh Youssefi ◽  
Patrick L. Gurian
Keyword(s):  
Solar Energy ◽  
Capital Investment ◽  
Supply And Demand ◽  
Price Volatility ◽  
The United States ◽  
Investment Model ◽  
Capital Investments ◽  
Demand Model ◽  
Market Prices ◽  
Investment Returns

Pennsylvania is one of a number of U.S. states that provide incentives for the generation of electricity by solar energy through Solar Renewal Energy Credits (SRECs). This article develops a return on investment model for solar energy generation in the PJM (mid-­Atlantic) region of the United States. Model results indicate that SREC values of roughly $150 are needed for residential scale systems to break even over a 25-­year project period at 3% interest. Market prices for SRECs in Pennsylvania have been well below this range from late 2011 through the first half of 2016, indicating that previous capital investments in solar generation have been stranded as a result of steep declines in the value of SRECs. A simple conceptual supply and demand model is developed to explain the sharp decline in market prices for SRECs. Also discussed is a possible policy remedy that would add unsold SRECs in a given year to the SREC quota for the subsequent year.

The impact of regulations on labor markets in the U.S.

2019 ◽  
Vol 1 (1) ◽  
pp. 36-40
Author(s):  
Souad Adnane
Keyword(s):  
Supply And Demand ◽  
Demand Model ◽  
Lead Teachers ◽  
Associate's Degree ◽  
Childcare Workers ◽  
Educational Requirements ◽  
The Cost ◽  
Women's Labor Force Participation ◽  
The Impact ◽  
The U.S

The District of Columbia (DC) Office of the Superintendent of Education (OSSE) issued in December 2016 new educational requirements for childcare workers, according to which, all childcare center directors in the District must earn a bachelor’s degree by December 2022 and all lead teachers an associate’s degree by December 2020 (Institute for Justice, 2018). Moreover, DC has one of the lowest staff-child ratios in the country. How are regulations pertaining to childcare workers’ qualifications and staff-child ratio affecting the childcare market in DC? The present paper is an attempt to answer this question first by analyzing the effects of more stringent regulations on the cost and availability of childcare in the U.S based on existing studies. It also uses the basic supply and demand model to examine the possible impact of the new DC policy on the cost, quality and supply of childcare in the District and how it will affect working parents, especially mothers. Next, the paper discusses the impact of deregulation based on simulations and regressions conducted by studies covering the U.S., and implications for quality. It concludes that more stringent childcare regulations, regarding educational requirements and staff-child ratios, are associated with a reduced number of childcare centers and a higher cost, and eventually affects women’s labor force participation.

An Aggregate-Demand Model for Automobiles

1965 ◽  
Vol 38 (3) ◽  
pp. 252 ◽  
Author(s):  
Thomas R. Dyckman
Keyword(s):  
Aggregate Demand ◽  
Demand Model

scholarly journals Endogenous On-Site Time in the Recreation Demand Model

1999 ◽  
Vol 75 (4) ◽  
pp. 603 ◽  
Author(s):  
Matthew D. Berman ◽  
Hong Jin Kim
Keyword(s):  
Recreation Demand ◽  
Demand Model

scholarly journals Self-Regulating Demand and Supply Equilibrium in Joint Simulation of Travel Demand and a Ride-Pooling Service

2021 ◽  
pp. 036119812199714
Author(s):  
Gabriel Wilkes ◽  
Roman Engelhardt ◽  
Lars Briem ◽  
Florian Dandl ◽  
Peter Vortisch ◽  
...  
Keyword(s):  
Real Time ◽  
Travel Demand ◽  
State Of The Art ◽  
Choice Model ◽  
Mode Choice ◽  
Attractive Alternative ◽  
Full Potential ◽  
Demand Model ◽  
Modeling Framework ◽  
Demand And Supply

This paper presents the coupling of a state-of-the-art ride-pooling fleet simulation package with the mobiTopp travel demand modeling framework. The coupling of both models enables a detailed agent- and activity-based demand model, in which travelers have the option to use ride-pooling based on real-time offers of an optimized ride-pooling operation. On the one hand, this approach allows the application of detailed mode-choice models based on agent-level attributes coming from mobiTopp functionalities. On the other hand, existing state-of-the-art ride-pooling optimization can be applied to utilize the full potential of ride-pooling. The introduced interface allows mode choice based on real-time fleet information and thereby does not require multiple iterations per simulated day to achieve a balance of ride-pooling demand and supply. The introduced methodology is applied to a case study of an example model where in total approximately 70,000 trips are performed. Simulations with a simplified mode-choice model with varying fleet size (0–150 vehicles), fares, and further fleet operators’ settings show that (i) ride-pooling can be a very attractive alternative to existing modes and (ii) the fare model can affect the mode shifts to ride-pooling. Depending on the scenario, the mode share of ride-pooling is between 7.6% and 16.8% and the average distance-weighed occupancy of the ride-pooling fleet varies between 0.75 and 1.17.

scholarly journals Sensitivity Analysis of Emission Models of Parcel Lockers vs. Home Delivery Based on HBEFA

2021 ◽  
Vol 18 (12) ◽  
pp. 6325
Author(s):  
Maren Schnieder ◽  
Chris Hinde ◽  
Andrew West
Keyword(s):  
New York ◽  
Road Transport ◽  
Emission Factors ◽  
Home Delivery ◽  
Demand Model ◽  
External Effects ◽  
Last Mile ◽  
Emission Models ◽  
Home Deliveries ◽  
Parcel Deliveries

Global concerns about the environmental effects (e.g., pollution, land use, noise) of last-mile deliveries are increasing. Parcel lockers are seen as an option to reduce these external effects of last-mile deliveries. The contributions of this paper are threefold: firstly, the research studies simulating the emissions caused by parcel delivery to lockers are summarized. Secondly, a demand model for parcel deliveries in New York City (NYC) is created for 365 days and delivery trips to lockers and homes are optimized for 20 “real-world” scenarios. Thirdly, using the emission factors included in the HandBook Emission Factors for Road Transport (HBEFA) database, the maximum percentage of customers who could pick up a parcel by car from parcel lockers that would result in fewer total emissions (driving customers + walking customers) than if home deliveries were adopted is calculated for various pollutants and scenario assumptions (i.e., street types, temperature, parking duration, level of service and vehicle drivetrain). This paper highlights how small changes in the calibration can significantly change the results and therefore using average values for emission factors or only considering one pollutant like most studies may not be appropriate.

Sign in / Sign up

Export Citation Format

Share Document