| Journal Article |
File Downloads |
Abstract Views |
| Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
| A Classification System for Economic Stochastic Control Models |
0 |
0 |
1 |
79 |
0 |
0 |
1 |
302 |
| APPROXIMATING THE VALUE FUNCTION FOR OPTIMAL EXPERIMENTATION |
0 |
0 |
0 |
3 |
0 |
0 |
3 |
22 |
| Active learning Monte Carlo results |
0 |
0 |
0 |
43 |
0 |
0 |
0 |
177 |
| Active learning: A correction |
0 |
0 |
0 |
14 |
0 |
0 |
0 |
112 |
| Are supercomputers useful for optimal control experiments? |
0 |
0 |
0 |
16 |
0 |
0 |
0 |
86 |
| Comparison of policy functions from the optimal learning and adaptive control frameworks |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
28 |
| Computational Economics: Help for the Underestimated Undergraduate |
0 |
0 |
0 |
87 |
0 |
0 |
1 |
275 |
| Computing the steady state of linear quadratic optimization models with rational expectations |
0 |
0 |
1 |
24 |
0 |
1 |
2 |
131 |
| Expected Optimal Feedback with Time-Varying Parameters |
0 |
0 |
0 |
4 |
0 |
0 |
0 |
50 |
| Guest Editorial: Special Issue on Experimentation in Economics |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
| Handbook of computational economics: H.M. Amman, D.A. Kendrick, J. Rust, (eds.), vol. 1. North-Holland, Amsterdam, 1996, pp. xxi + 827, $163.75/265.0 Dutch Guilders. (ISBN 0-444-89857-3) |
0 |
0 |
0 |
69 |
0 |
0 |
2 |
279 |
| How Active is Active Learning: Value Function Method Versus an Approximation Method |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
7 |
| Implementing stochastic control software on supercomputing machines |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
78 |
| LINEAR-QUADRATIC OPTIMIZATION FOR MODELS WITH RATIONAL EXPECTATIONS |
0 |
0 |
0 |
20 |
0 |
0 |
1 |
79 |
| Land tenure and conflict resolution: a game theoretic approach in the Narok district in Kenya |
0 |
0 |
0 |
47 |
1 |
1 |
3 |
264 |
| Learning-by-Doing under Uncertainty |
0 |
0 |
1 |
71 |
0 |
0 |
1 |
371 |
| Mitigation of the Lucas critique with stochastic control methods |
0 |
0 |
0 |
55 |
0 |
0 |
0 |
179 |
| Mitigation of the Lucas critique with stochastic control methods |
0 |
0 |
0 |
7 |
0 |
1 |
2 |
57 |
| Modeling Instrumental Rationality, Land Tenure and Conflict Resolution |
0 |
0 |
0 |
70 |
0 |
0 |
0 |
440 |
| Nonconvexities in Stochastic Control Models |
0 |
0 |
0 |
34 |
0 |
0 |
0 |
245 |
| Numerical solutions of the algebraic matrix Riccati equation |
1 |
1 |
1 |
324 |
1 |
1 |
1 |
928 |
| Programming Languages in Economics |
0 |
0 |
0 |
394 |
0 |
1 |
1 |
1,285 |
| Quarterly Fiscal Policy |
0 |
0 |
0 |
13 |
0 |
0 |
0 |
47 |
| Robust Evolutionary Algorithm Design for Socio-Economic Simulation: A Correction |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
73 |
| Robust Evolutionary Algorithm Design for Socio-economic Simulation |
0 |
0 |
0 |
69 |
0 |
0 |
1 |
387 |
| Should Macroeconomic Policy Makers Consider Parameter Covariances? |
0 |
0 |
0 |
34 |
1 |
1 |
1 |
284 |
| Solving stochastic optimization models with learning and rational expectations |
0 |
0 |
0 |
36 |
0 |
0 |
0 |
143 |
| Special issue in honor of Berç Rustem |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
31 |
| Stochastic Policy Design in a Learning Environment with Rational Expectations |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
10 |
| Summaries |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
131 |
| Teaching Macroeconomics with GAMS |
0 |
0 |
3 |
253 |
0 |
0 |
4 |
825 |
| The JEDC and computational economics |
0 |
0 |
0 |
28 |
2 |
4 |
5 |
318 |
| The parameter set in an adaptive control Monte Carlo experiment: Some considerations |
0 |
0 |
0 |
12 |
0 |
0 |
0 |
78 |
| The work of David Kendrick |
0 |
0 |
0 |
16 |
0 |
0 |
1 |
145 |
| What Is Computational Economics? |
0 |
1 |
2 |
74 |
0 |
2 |
3 |
253 |
| Total Journal Articles |
1 |
2 |
9 |
1,945 |
5 |
12 |
33 |
8,123 |
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