The Effectiveness of Parametric Approximation: A Case of Mainframe Computer Investment
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The general method to solve the fixed point problem is a discretization of observed state variables. When the observed state variable is continuous, the required fixed point is in fact an infinite dimensional object. Therefore, in order to solve the fixed point problem, it is necessary to discretize the state space so that the state variable takes on only finitely many values. But there are limits regarding this method: (i) "curse of dimensionality"; (ii) the limits it places on our ability to solve high-dimensional DP problems. Despite these limits, this method have been used in many literature. However, The discretization method may not be applicable to computer replacement research to solve the fixed point problem, because of the aforementioned problems. Using a detailed data set on computer holdings by one of the world's largest telecommunication companies, this paper shows the effectiveness of Parametric Approximation procedure by comparison with the discretization method, which converts the contraction fixed-point problem into a nonlinear least squares problem with combining maximum likelihood estimation method to estimate the unknown parameters.
Abstract
The general method to solve the fixed point problem is a discretization of observed state variables. When the observed state variable is continuous, the required fixed point is in fact an infinite dimensional object. Therefore, in order to solve the fixed point problem, it is necessary to discretize the state space so that the state variable takes on only finitely many values. But there are limits regarding this method: (i) "curse of dimensionality"; (ii) the limits it places on our ability to solve high-dimensional DP problems. Despite these limits, this method have been used in many literature. However, The discretization method may not be applicable to computer replacement research to solve the fixed point problem, because of the aforementioned problems. Using a detailed data set on computer holdings by one of the world's largest telecommunication companies, this paper shows the effectiveness of Parametric Approximation procedure by comparison with the discretization method, which converts the contraction fixed-point problem into a nonlinear least squares problem with combining maximum likelihood estimation method to estimate the unknown parameters.
참고문헌 (26)
- Billingsley, Patrick, "Probability and Measure", pp.309~310 (1979), John Wiley
- Cho, S., "An Empirical Model of Mainframe Computer Investment", Journal of Applied Econometrics forthcoming (2007)
- Cho, S., "Is Econometrics Useful for Private Policy Making? A Case Study of Replacement Policy at an Auto Rental Company", forthcoming Journal of Econometrics (2008)
- Cox, D. R., "Partial Likelihood", Biometrika, 62, pp.269~276 (1975)
- Cox, D. R., "Theoretical Statistics" (1974), Chapman and Hall
- Feldstein, M.S., "Towards an Economic Theory of Replacement Investment", Econometrica, 42, pp.393~423 (1974)
- Gandal, Neil, "Adoptions and Orphans in the Early Microcomputer Market", forthcoming Journal of Industrial Economics (1998)
- Greenstein, Shane M., "Dynamic Modeling of The Product Life Cycle in The Commercial Mainframe Computer Market, 1968-1982" (1997), Working paper 6124, NBER
- Hall, George, "An Empirical Model of Inventory Investment by Durable Commodity" (1999), Intermediaries, Department of Economics, Yale University
- Heckman, J. J., "Statistical Models for Discrete Panel Data, in Structural Analysis of Discrete Data with Econometric Applications" (1981), M.I.T. Press
- Kennet, D. Mark, "A StructuralModel of Aircraft engineMaintenance", Journal of Applied Econometrics, 9, pp.351~68 (1994)
- Khanna, Tarun, "Racing Behavior: Technological Evolution in the High-End Computer Industry" (1993)
- Klette, Tor Jacob, "Empirical Patterns of firm Growth and R&D Investment: A Quality Ladder Model Interpretation" (1998), NBER Working Paper 6753
- McFadden, Daniel, "Conditional Logit Analysis of Qualitative ChoiceBehavior in : Frontiers of Economics" (1973), Academic Press
- McFadden, Daniel, "Econometric Models of Probabilistic Choice in : Structural Analysis of Discrete Data" (1981), M.I.T Press
- Miller, R., "Job Matching and Occupational Choice", Journal of PoliticalEconomy, 92, pp.1086~1120 (1984)
- Montemerlo, Michael S., "Technologies andDesigns for Electronic Nanocomputers" (1996), MITRE MSR Program
- Perska-Juliussen, Karen, "The 8th Annual ComputerIndustry Almanac" (1997), Computer Industry Almanac Inc
- Pierskalla, W. P., "A survey of Maintenance Models:The Control and Surveillance of Deteriorating Systems", NavalResearch Logistics Quarterly, 23, pp.353~388 (1976)
- Rust, John, "Stationary Equilibrium in a Market for Durable Assets", Econometrica, 53, pp.733~806 (1985)
- Rust, John, "When is it Optimal to kill off the Market for Used DurableGoods", Econometrica, 54, pp.65~86 (1986)
- Rust, John, "Optimal Replacement of GMC Bus engine: An Empirical Modelof Harold Zurcher", Econometrica, 55, pp.999~1033 (1987)
- Rust, John, "Maximum Likelihood Estimation of Discrete Control Processes", SIAM Journal of Control and Optimization, 26, pp.1006~1024 (1988)
- Rust, John, "National Bureau of EconomicResearch" (1988), University of Chicago Press
- Rust, John, "Nested Fixed Point Algorithm Document Manual" (1995), v5
- Sherif,Y.S., "Optimal Maintenance Models for SystemSubject to Failure- A Review", Naval Research Logistics Quarterly, 32, pp.47~74 (1999), SIA Annual databook, Semiconductor Industry Association