Thu.2 10:45–12:00 | H 3004 | APP
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Applications in Economics

Chair: Po-An Chen
10:45

Benteng Zou

joint work with Luisito Bertinelli, Stephane Poncin

The Dynamics Competition of Key Elements of Sustainable Technology -- the Rare Earth Elements

Rare earth elements are widely uses of i-phones, computers, hybrid cars, wind and solar energy and are essentially important for the worldwide sustainable development. Few has been done related to rare earth elements competition in economic research. This current study tries to fill in this gap. A monopoly to duopoly competition is constructed and studied. We provide necessary and sufficient conditions when should enter the competition and what would be the consequences and response of China. We also provide the analysis if cooperation between China and USA is possible.

11:10

Asiye Aydilek

joint work with Harun Aydilek

Do we really need heterogenous agent models under recursive utility?

We investigate the existence of representative agent under various heterogeneities in a recursive utility framework. We provide the analytical solution of household allocations. We numerically explore whether we can find a representative agent whose income is the aggregate income of the society and whose allocations are the aggregate allocations of the society under heterogeneity in the parameter of risk aversion and/or parameter of intertemporal substitution, or discount rate or survival probability. We find that there is no representat

11:35

Po-An Chen

joint work with Chi-Jen Lu, Yu-Sin Lu

An Alternating Algorithm for Finding Linear Arrow-Debreu Market Equilibrium

Jain reduced equilibrium computation in Arrow-Debreu (AD) markets to that in bijective markets. Motivated by the convergence of mirror-descent algorithms to market equilibria in linear Fisher markets, we simply design algorithms to solve a rational convex program for linear bijective markets in this paper. Our algorithm for computing linear AD market equilibrium is based on solving the rational convex program formulated by Devanur et al., repeatedly alternating between a step of gradient-descent-like updates and a follow-up step of optimization. Convergence can be achieved by a new analysis.