John Rust

• Economic and Health Determinants of Retirement Behavior
  Current (2004-07-01 - 2009-06-30)
  NIA/RAND
  Abstract

  The program project brings together new data, a large group of experienced researchers from different countries, and a number of different modeling approaches to improve our understanding of retirement decisions. The overriding goal of the program project is to provide a far more complete, and perhaps more subtle, picture of what makes people reduce their work effort late in life than we have today. In view of the major issues faced by several countries with respect to the nature and future sustainability of old age security systems, a secondary important goal is to provide information that can guide policy makers in designing or changing these systems. The program project will contain six component projects and two cores. The component projects deal respectively with:(Blundell) the timing and coordination of retirement of spouses; (Hurd) the role of wealth accumulation or decumulation on retirement timing: (Gustman) the measurement of pension outcomes, including how much people actually know about their prospective pensions and about the changes in these pensions; (Rust) forward looking models of retirement timing, with special emphasis on D1 and SSI application; (Kapteyn) the role of health and workplace conditions in retirement decisions; (Kapteyn) integration of the findings and approaches in the first six projects, including an evaluation of the relative importance of different explanatory factors, the empirical success of different modeling approaches and several forms of new data that may aid in improving our empirical models. The data core provides overall programming support, maintains a number of important databases to be used by all component projects, and facilitates the sharing of software across projects. The administrative core facilitates interaction and guarantees a smooth administrative process. Integration of different projects is achieved by bi-annual workshops, common procedures imposed by the integrative project, by researchers working on different component projects and the organization of discussion boards.

• Collaborative Research on Models of Bargaining and Price Determinantion of residential Real Estate, With and Without Real Estate Agents
  Current (2006-08-01 - 2009-07-31)
  NSF
  Abstract

  Residential real estate accounts for a large share of wealth and GDP in modern economies. In addition, the majority of households own their homes and the sale and/or the purchase of a home is often the largest financial transaction a household engages in. Surprisingly, there are few models available to analyze the housing transaction process. This research will study the transaction process in the housing market. It will develop computationally tractable models of the behavior of buyers, sellers, and intermediaries in the housing market, and estimate the models using a high frequency micro data on individual housing transactions, which include how list prices are revised over time, information on each visit by buyers, and outcomes of bargaining for a large sample of homes over a long period of time the PIs will collect in both the US and the UK. The model has 3 agents---seller, buyers, and real estate agents who interact in several bargaining rounds. Real estate agents are modeled as having access to a technology and data (the MLS) that can increase the arrival rate of buyers as well as match potential buyers to sellers.

  This research extends, applies, and empirically implements theories of dynamic decision making and bargaining under incomplete information to the housing market, in order to describe the operation and efficiency of these large markets. This is the first attempt to apply dynamic decision making to the housing market, a significant contribution to the existing literature. Understanding the transaction process in the housing market is important in itself. In addition, there are potential public policy benefits resulting from better analytical models of the residential real estate market. For example, the U.S. Department of Justice is currently investigating the U.S. National Association of Realtors to determine whether it has created unfair barriers to entry, particularly in restricting access to the MLS, in order to maintain large real estate commissions. The result of this research could be very useful in such litigation.

  The analysis will be extended to include other real estate intermediaries and an endogenous choice of whether to sell via a real estate agency, or to sell by owner. This will allow researchers industrial organizational issues connected with real estate agents, including endogenous determination of real estate contracts and commissions. Using data from both the US and the UK allows the PIs to shed light on institutions, laws, and customs affect the relative efficiency of different forms of organization of the housing market. The results from this research should also help households and real estate agents understand the trade-offs at play when formulating home selling or buying strategies.

• Optimal Harvesting of Timber: Valuing Timberland with Stochastically Evolving Timber Volume and Prices Using Linked Biological/Geographical Data from British Columbia
  Current (2003-07-01 - 2007-06-30)
  NSF
  Abstract

  In environmental and natural resource economics, the management of renewable natural resources is of considerable interest to economists because the prospect of stewarding a resource forever has practical importance and real-world relevance. Moreover, because past failures in managing certain renewable natural resources properly have lead to the extinction of several species, developing practical strategies for managing remaining renewable natural resources is both timely and useful. This project investigates in detail the management of one renewable natural resource, timber, in the province of British Columbia, Canada.

  For a Timber Supply Area (TSA) in British Columbia the investigators have obtained unique access to extremely detailed site-level data, which are used by timber-supply managers in the British Columbia Ministry of Forests when making harvesting decisions. In particular, they have access to elaborate linked biological and geographical data in the form of a Geographical Information System (GIS) at the grid level which, in this case, is a hectare or 100 meters square. Thus, for every hectare in the Fraser TSA, which is located near Vancouver, British Columbia and contains several hundreds of thousands hectares, officials at the Ministry of Forests provide the investigators with a wide variety of biological, engineering, and geographical information relevant to harvesting timber. In addition, they also have access to the harvesting strategies proposed and, in some cases, the decisions implemented by the Minister of Forests, so they can compare our estimated decisions with actual ones.

  In developing practical harvesting solutions for timber, they apply the method of stochastic dynamic programming. The goal of the project is to make the following contributions: First, this project takes geography seriously, both in the planar sense and in the three-dimensional sense. Second, it takes site-specific heterogeneity seriously both on the cost side in terms of felling and transportation and on the growth and yield side in terms of heterogeneous stands of timber. Third, it models initial conditions. In particular, it does not take as the starting point a steady-state allocation, or even an optimal allocation. Instead, it takes the existing uneven-aged timber stand as given and derives the optimal policy function, the optimal timber-harvesting profile, in terms of this age distribution. Fourth, this project uses best-practice biological methods to model the dynamics of uneven-aged forest growth and yield. Fifth, in the past economists and foresters have typically demonstrated their methods by making extremely simple assumptions concerning the stochastic nature of timber prices and volumes so that closed-form examples could be solved. This research implements recent developments in computational methods so that practitioners can solve numerically for the optimal policy function in realistic biological, economic, and spatial environments.

• Characterizing Efficient Social Insurance Institutions: Theory and Computation
  Current (2002-08-01 - 2007-07-31)
  NSF
  Abstract

  This research will develop theoretical and computational approaches for characterizing efficient social insurance institutions. We define a social insurance institution as a compulsory government-run program that provides a set of state-contingent taxes (premiums or contributions) and transfers (benefits) that cover a well-defined set of risks. An efficient social insurance institution is one that provides a given level welfare to the individuals in the system at minimal cost. Our research will attempt to provide characterizations of efficient social insurance institutions that cover the following risks: 1) longevity, via mandatory pensions or "old age insurance", 2) disability, via disability insurance, 3) unemployment, via unemployment insurance, and 4) health care costs, via medical insurance. Another objective of social insurance is lifetime redistribution of income and/or wealth. This can be viewed as insurance for a fifth class of risks, namely insurance for individuals who have certain fixed characteristics or "types" that may lead to permanently lower lifetime employment, earnings, wealth, and welfare. Social insurance programs are large and pervasive in developed economies. In the U.S., spending on Social Security (Old Age, Disability, and Unemployment Insurance), Medicare, Medicaid amounted to 48.3\% of total Federal spending and 9.8\% of GDP in 2000 (U.S. Congressional Budget Office). All forecasts indicate that unless benefits are reduced, social insurance spending will grow rapidly over the coming decades as the baby boomers age and start to retire. Although there have been proposals to shift the costs of social insurance from the government to the private sector via various "privatization" schemes, a variety of moral hazard and adverse selection problems hinder the operation of private insurance markets. We take market incompleteness as the principal rationale for mandatory government provision of insurance, and as the basic point of departure for our analysis. We assume that the government can compel universal participation, but we also assume that it faces the same informational constraints as private insurance institutions would face if they existed. We deal with these fundamental informational asymmetries via two very different but related strategies: 1) a "dynamic mechanism design" (DMD) approach where we search for an efficient policy over an infinite-dimensional space of all possible policies that satisfy certain participation and incentive constraints, and 2) a "parametric mechanism design" (PMD) approach where we search for an "approximately efficient" social insurance institution in a finite-dimensional subspace of social insurance institutions and where incentive constraints are ignored.

  Using these techniques we will not only be able to characterize the form of efficient social insurance institutions, we will also be able to quantify the degree of inefficiency in current social insurance institutions. We expect to be able to characterize optimal social security and disability insurance programs as part of a comprehensive, integrated analysis of social insurance in the U.S. and other developed economies. Given the large share of GDP devoted to social insurance, the potential cost savings from discovering more efficient social insurance programs provides a strong, practical rationale for this research.

• Modeling the Impact of Health Insurance on Retirement
  Ended (2003-07-03 - 2005-09-30)
  U Michigan