Two-stage network design in humanitarian logistics.

Natural disasters such as floods and earthquakes can cause multiple deaths, injuries, and severe damage to properties. In order to minimize the impact of such disasters, emergency response plans should be developed well in advance of such events. Moreover, because different organizations such as non-governmental organizations (NGOs), governments, and militaries are involved in emergency response, the development of a coordination scheme is necessary to efficiently organize all the activities and minimize the impact of disasters. The logistics network design component of emergency management includes determining where to store emergency relief materials, the corresponding quantities and distribution to the affected areas in a cost effective and timely manner. In a two-echelon humanitarian relief chain, relief materials are pre-positioned first in regional rescue centers (RRCs), supply sources, or they are donated to centers. These materials are then shipped to local rescue centers (LRCs) that distribute these materials locally. Finally, different relief materials will be delivered to demand points (also called affected areas or AAs). Before the occurrence of a disaster, exact data pertaining to the origin of demand, amount of demand at these points, availability of routes, availability of LRCs, percentage of usable pre-positioned material, and others are not available. Hence, in order to make a location-allocation model for pre-positioning relief material, we can estimate data based on prior events and consequently develop a stochastic model. The outputs of this model are the location and the amount of pre-positioned material at each RRC as well as the distribution of relief materials through LRCs to demand points. Once the disaster occurs, actual values of the parameters we seek (e.g., demand) will be available. Also, other supply sources such as donation centers and vendors can be taken into account. Hence, using updated data, a new location-allocation plan should be developed and used. It should be mentioned that in the aftermath of the disaster, new parameters such as reliability of routes, ransack probability of routes and priority of singular demand points will be accessible. Therefore, the related model will have multiple objectives. In this dissertation, we first develop a comprehensive pre-positioning model that minimizes the total cost while considering a time limit for deliveries. The model incorporates shortage, transportation, and holding costs. It also considers limited capacities for each RRC and LRC. Moreover, it has the availability of direct shipments (i.e., shipments can be done from RRCs directly to AAs) and also has service quality. Because this model is in the class of two-stage stochastic facility location problems, it is NP-hard and should be solved heuristically. In order to solve this model, we propose using Lagrangian Heuristic that is based on Lagrangian Relaxation. Results from the first model are amounts and locations of pre-positioned relief materials as well as their allocation plan for each possible scenario. This information is then used as a part of the input for the second model, where the facility location problem will be formulated using real data. In fact, with pre-positioned items in hand, other supplies sources can be considered as necessary. The resulting multi-objective problem is formulated based on a widely used method called lexicography goal programming. The real-time facility location model of this dissertation is multi-product. It also considers the location problem for LRCs using real-time data. Moreover, it considers the minimization of the total cost as one of the objectives in the model and it has the availability of direct shipments. This model is also NP-hard and is solved using the Lagrangian Heuristic. One of the contributions of this dissertation is the development of Lagrangian Heuristic method for solving the pre-positioning and the real- time models. Based on the results of Lagrangian Heuristic for the pre-positioning model, almost all the deviations from optimal values are below 5%, which shows that the Heuristics works acceptably for the problem. Also, the execution times are no more than 780 seconds for the largest test instances. Moreover, for the real-time model, though not directly comparable, the solutions are fairly close to optimal and the execution time for the largest test instance is below 660 seconds. Hence, the efficiency of the heuristic for real-time model is satisfactory

Multi-Period Trading via Convex Optimization

We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk, transaction cost and holding cost such as the borrowing cost for shorting assets. We then describe a multi-period version of the trading method, where optimization is used to plan a sequence of trades, with only the first one executed, using estimates of future quantities that are unknown when the trades are chosen. The single-period method traces back to Markowitz; the multi-period methods trace back to model predictive control. Our contribution is to describe the single-period and multi-period methods in one simple framework, giving a clear description of the development and the approximations made. In this paper we do not address a critical component in a trading algorithm, the predictions or forecasts of future quantities. The methods we describe in this paper can be thought of as good ways to exploit predictions, no matter how they are made. We have also developed a companion open-source software library that implements many of the ideas and methods described in the paper

The Paper Chase: Securitization, Foreclosure, and the Uncertainty of Mortgage Title

The mortgage foreclosure crisis raises legal questions as important as its economic impact. Questions that were straightforward and uncontroversial a generation ago today threaten the stability of a $13 trillion mortgage market: Who has standing to foreclose? If a foreclosure was done improperly, what is the effect? And what is the proper legal method for transferring mortgages? These questions implicate the clarity of title for property nationwide and pose a too-big-to-fail problem for the courts. The legal confusion stems from the existence of competing systems for establishing title to mortgages and transferring those rights. Historically, mortgage title was established and transferred through the public demonstration regimes of UCC Article 3 and land recordation systems. This arrangement worked satisfactorily when mortgages were rarely transferred. Mortgage finance, however, shifted to securitization, which involves repeated bulk transfers of mortgages. To facilitate securitization, deal architects developed alternative contracting regimes for mortgage title: UCC Article 9 and MERS, a private mortgage registry. These new regimes reduced the cost of securitization by dispensing with demonstrative formalities, but at the expense of reduced clarity of title, which raised the costs of mortgage enforcement. This trade-off benefitted the securitization industry at the expense of securitization investors because it became apparent only subsequently with the rise in mortgage foreclosures. The harm, however, has not been limited to securitization investors. Clouded mortgage title has significant negative externalities on the economy as a whole. This Article proposes reconciling the competing title systems through an integrated system of note registration and mortgage recordation, with compliance as a prerequisite to foreclosure. Such a system would resolve questions about standing, remove the potential cloud to real-estate title, and facilitate mortgage financing by clarifying property rights

Financial Market Frictions

Defined simply as anything that interferes with trade, financial market frictions can exist even in efficient markets. Understanding financial market frictions is important, this article argues, because they generate real costs to investors, because they generate business opportunities, and because they change over time. Financial market frictions depend in part on market structure. Market structure tends to evolve over time, as trading volume increases, from low fixed costs and high marginal costs to high fixed costs and low marginal costs. To help identify the best means of reducing market frictions costs, the authors classify and discuss five primary categories of frictions: transactions costs, taxes and regulations, asset indivisibility, nontraded assets, and agency and information problems. Looking for evidence of how frictions influence market participants behavior, the authors not only review the economic literature but also conduct an empirical exercise to illustrate and quantify frictions impact on investors risk-return trade-off. Their results show that market frictions impose utility costs on investors by making preferable investment portfolios unattainable. Their findings and other academic studies also suggest that investors who ignore market frictions compound the harm done by the frictions themselves

The Effects of Intermarriage on the Earnings of Female Immigrants in the United States

This paper investigates the effects of intermarriage on the earnings of female immigrants in the United States. The main empirical question asked is whether immigrant females married to US-born spouses have higher earnings than those of immigrant females married to other immigrants. Using 1970 and 1870 samples of IPUMS data, I estimate an earnings equation through OLS. I also correct for the labor force selection bias using the Heckman procedure. I finally take into account the endogeneity of intermarriage and apply a twostage least squares (2SLS) estimation procedure. I find that there is a positive marriage premium among immigrant females in the United States but a negative intermarriage premium for exogamously married females compared to endogamously married females. My results show that the longer the immigrant stays in the host country, the higher her wages, which is evidence for the assimilation effect over time. I find some evidence for a negative labor force selection bias among immigrant females. In other words, higher human capital women may select themselves out of the labor force, while lower human capital women are working for wages. Among those who are in the labor force, however, married females earn more than singles. I also conclude that being an immigrant from an English-speaking country does not have any impact on wages. Both premiums become statistically insignificant in difference from zero when 2SLS is used as an estimation procedure

Multilateral Transparency for Security Markets Through DLT

For decades, changing technology and policy choices have worked to fragment securities markets, rendering them so dark that neither ownership nor real-time price of securities are generally visible to all parties multilaterally. The policies in the U.S. National Market System and the EU Market in Financial Instruments Directive— together with universal adoption of the indirect holding system— have pushed Western securities markets into a corner from which escape to full transparency has seemed either impossible or prohibitively expensive. Although the reader has a right to skepticism given the exaggerated promises surrounding blockchain in recent years, we demonstrate in this paper that distributed ledger technology (DLT) contains the potential to convert fragmented securities markets back to multilateral transparency. Leading markets generally lack transparency in two ways that derive from their basic structure: (1) multiple platforms on which trades in the same security are matched have separate bid/ask queues and are not consolidated in real time (fragmented pricing), and (2) highspeed transfers of securities are enabled by placing ownership of the securities in financial institutions, thus preventing transparent ownership (depository or street name ownership). The distributed nature of DLT allows multiple copies of the same pricing queue to be held simultaneously by a large number of order-matching platforms, curing the problem of fragmented pricing. This same distributed nature of DLT would allow the issuers of securities to be nodes in a DLT network, returning control over securities ownership and transfer to those issuers and thus, restoring transparent ownership through direct holding with the issuer. A serious objection to DLT is that its latency is very high—with each Bitcoin blockchain transaction taking up to ten minutes. To remedy this, we first propose a private network without cumbersome proof-of-work cryptography. Second, we introduce into our model the quickly evolving technology of “lightning networks,” which are advanced two-layer off-chain networks conducting high-speed transacting with only periodic memorialization in the permanent DLT network. Against the background of existing securities trading and settlement, this Article demonstrates that a DLT network could bring multilateral transparency and thus represent the next step in evolution for markets in their current configuration

Transaction based indices for the UK commercial property market : exploration and evaluation using IPD data

Publisher PD