Demand Estimation of Proposed Bus Rapid Route in Al Kut City

Public transit in the city of Al-Kut faces great challenges due to the weakness of the local government abilities in providing adequate conditions for public transport such as wide vehicles, comfortable seats, and other environmentally friendly means of transport that are almost non-use in the city of Kut, where the dependence is heavily on Mini Bus (Kia) and a medium-sized bus, most of which are old, do not operate in an integrated way, compete with each other for the passengers, reduce the flexibility of movement. This study attempts to estimate the demand for the proposed bus rapid route in the city of al Kut as a modern public transport that can contribute to reducing congestion in the city. In this study, the demand for the current public transport network lines in the city was studied, which are 12 lines using boarding / alighting values to determine passenger loads and assess flow on each route in the transportation network using the origin-destination (OD) data from on/off data, then repeat the application on the BRT route, this was done using assignment model in TransCAD software, where the results showed an estimated value for passenger demand on BRT route about 7,616 passengers/hour, which is equivalent to 40.12 % of the transport lines service.

Durable Goods Adoption and the Consumer Discount Factor: A Case Study of the Norwegian Book Market

We exploit a change in Norway’s fixed book pricing policies to construct exclusion restrictions with which to identify consumers’ discount factor. We assume that the policy change generated an unanticipated, exogenous shock to consumers’ expectations about future price cuts. Our findings suggest that consumers are much more impatient than would be implied by the real rate of interest, challenging the standard assumed rate of discounting in the extant literature on dynamic demand estimation. The high rate of consumer impatience is consistent with laboratory studies in the behavioral economics and decision-making literatures. This paper was accepted by Matthew Shum, marketing.

Sensor Deployment Strategy and Traffic Demand Estimation with Multisource Data

Since traffic origin-destination (OD) demand is a fundamental input parameter of urban road network planning and traffic management, multisource data are adopted to study methods of integrated sensor deployment and traffic demand estimation. A sensor deployment model is built to determine the optimal quantity and locations of sensors based on the principle of maximum link and route flow coverage information. Minimum variance weighted average technology is used to fuse the observed multisource data from the deployed sensors. Then, the bilevel maximum likelihood traffic demand estimation model is presented, where the upper-level model uses the method of maximum likelihood to estimate the traffic demand, and the lower-level model adopts the stochastic user equilibrium (SUE) to derive the route choice proportion. The sequential identification of sensors and iterative algorithms are designed to solve the sensor deployment and maximum likelihood traffic demand estimation models, respectively. Numerical examples demonstrate that the proposed sensor deployment model can be used to determine the optimal scheme of refitting sensors. The values estimated by the multisource data fusion-based traffic demand estimation model are close to the real traffic demands, and the iterative algorithm can achieve an accuracy of 10−3 in 20 s. This research has significantly promoted the effects of applying multisource data to traffic demand estimation problems.

Determinants of inorganic fertilizer use by smallholder farmers in South Wollo and Oromia special administrative zones, Ethiopia

The study investigated the determinants of fertilizer use by smallholder farmers. Data were drawn from 207 smallholder farmers, experts, and respective office heads using structured and semi-structured interview schedules, Key informant interviews and focus group discussions. Data were analysed using percentage, mean and standard deviation and linear regression model. About 94% of the farmers had the willingness to apply inorganic fertilizer on their farmland. An increasing price of inorganic fertilizer (96%), poor demand estimation (82%), delay in distribution (78%), lack of attention for the irrigation production system (65%), and unfair distribution/nepotism (61%) are the top-ranked challenges affecting inorganic fertilizer use. The existence of more active labour forces in the family (dy/dx = 20.4, t = 2.49), farmsize (dy/dx = 14.53, t = 3.82), ownership (dy/dx = 75 .13, t = 10.64), total income (dy/dx = 0.00024, t = 2.24), use of credit service (dy/dx = 31.11, t = 1.94), and frequency of extension contact (dy/dx = 24.60, t = 2.07), were found significantly promoting the amount of fertilizer use by smallholder farmers. Actions such as real demand estimation, arranging agricultural implements, and fertilizer subsidy for resource-poor farmers should be implemented to ensure food self-sufficiency.

An Efficient Approach For the Nodal Water Demand Estimation in Large-Scale Water Distribution Systems

Real-time modeling of the water distribution system (WDS) is a critical step for the control and operation of such systems. The nodal water demand as the most important time-varying parameter must be estimated in real-time. The computational burden of nodal water demand estimation is intensive, leading to inefficiency for the modeling of the large-scale network. The Jacobian matrix computation and Hessian matrix inversion are the processes that dominate the main computation time. To address this problem, an approach to shorten the computational time for the real-time demand estimation in the large-scale network is proposed. The approach can efficiently compute the Jacobian matrix based on solving a system of linear equations, and a Hessian matrix inversion method based on matrix partition and Iterative Woodbury-Matrix-Identity Formula is proposed. The developed approach is applied to a large-scale network, of which the number of nodal water demand is 12523, and the number of measurements ranging from 10 to 2000. Results show that the time consumptions of both Jacobian computation and Hessian matrix inversion are significantly shortened compared with the existing approach.

Endogenous Vertical Differentiation, Variety, and the Unequal Gains from Trade

How unequal are the gains from trade? This paper develops a structural framework to quantify the consequences of international trade on welfare of consumers across the income distribution, allowing for non-homothetic demand and endogenous quality choices by firms. Using random coefficients demand estimation techniques, I infer demand and supply parameters, as well as household-specific price indexes for more than 3,000 distinct industries and find the gains from trade to be moderately unequal except in wealthier and small economies. Further, not accounting for endogenous vertical differentiation would overstate the impact of trade on cost-of-living inequality by close to 50%.