Download presentation

Presentation is loading. Please wait.

Published byHelen Rho Modified over 2 years ago

1
Estimation of Life-Cycle Consumption Zhe Li (PhD Student) Stony Brook University

2
Introduction A CLASSICAL METHOD of moments estimator Instead using analytically form, replace the expected response function by a simulation result ---- the method of simulated moments (MSM). An application of MSM to life-cycle consumption model (Gourinchas and Parker (2002)).

4
Model Live t= 0----N, and work for periods T

5
Model When working Income Transitory shock: takes 0 with probability and otherwise. Permanent shock:

6
Model After retirement, no uncertainty. Illiquid wealth in the first year of retirement Retirement value function Consumption Rule (Merton (1971))

7
Solution Normalization At retirement When working

8
Solution In the last period of working In periods

9
Numerical method Intertemporal budget constraint Two-dimensional Gauss-Hermite quadrature

10
Simulation ParametersDescriptionValue Rate of time preference0.96 Rate of risk aversion0.514, where h is the ratio of illiquid wealth to the permanent component of income at retirement 0.001 Marginal propensity to consume at retirement0.071 RInterest rate1.0344 pProbability of unemployment0.00302 Variance of permanent shock0.0212 Variance of transitory shock0.0440 Initial log normalized wealth at age 26-2.794 (1.784)

16
Estimation Objective Two step MSM: The first subset: The second subset: Expectation of log consumption, Approximation (Monte-Carlo)

17
Estimation Find that minimize Where W is a T*T weighting matrix: –Inverse of the sample counterpart of –Corrected by the variance-covariance matrix for the first-stage estimation

18
Estimation Method Start at a point x in N-dimensional space, and proceed from there in some vector direction p Any function of N variables f(x) can be minimized along the line p, say finding the scalar a that minimizes f(x+ap) Replace x by x+ap, and start a new iteration until convergence occurs Example: Newton method

19
Estimation method This study, –x is the set of parameters –Dimension is T (time periods) –Objective function is –Gradient –Hessian matrix

20
Estimation Results Parameters Trust-Region Newton L-MQuasi-NewtonGlobal convergence 0.95970.95950.95110.9637 (0.0390)(0.0385)(0.0313)(0.0556) 0.49810.52360.94110.2008 (3.9409)(2.6876)(3.6892)(5.0803) Retirement Rule: 0.01160.00010.10690.0511 (7.3221)(6.7996)(6.5953)(1.8346) 0.07650.08220.06500.0895 (0.6604)(0.6086)(0.3639)(0.4741) fmin0.06860.06520.07720.0924 177.8519169.1142200.1481239.5556

Similar presentations

OK

L12 Uncertainty. Model with real endowments 1. Labor Supply (Labor-Leisure Choice) 2. Intertemporal Choice (Consumption-Savings Choice) 3. Uncertainty.

L12 Uncertainty. Model with real endowments 1. Labor Supply (Labor-Leisure Choice) 2. Intertemporal Choice (Consumption-Savings Choice) 3. Uncertainty.

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Ppt on various layers of the earth Ppt on hr practices of wipro Ppt on non ferrous minerals definition Ppt on regional political parties in india Ppt on online banking system Ppt on biogas power plant Ppt on hplc method development and validation Ppt on central administrative tribunal bench Ppt online for free Ppt on child labour download