Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach

In April 2003 the U.S. Federal Energy Regulatory Commission (FERC) proposed the Wholesale Power Market Platform (WPMP) for common adoption by U.S. wholesale power markets. The WPMP is a complicated market design that has been adopted in some regions of the U.S. but resisted in others on the grounds that its reliability has not yet been sufficiently tested. This article reports on the development of an agent-based computational framework for exploring the economic reliability of the WPMP. The key issue under study is the extent to which the WPMP is capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain advantage through strategic pricing, capacity withholding, and/or induced transmission congestion. Related work can be accessed at: http://www.econ.iastate.edu/tesfatsi/AMESMarketHome.htm

Discrete Double Auctions with Artificial Adaptive Agents: A Case Study of an Electricity Market Using a Double Auction Simulator

A key issue raised by previous researchers is the extent to which learning versus market structure is responsible for the high efficiency regularly observed for the double auction in human-subject experiments. In this study, a computational discrete double auction with discriminatory pricing is tested regarding the importance of learning agents for ensuring market efficiency. Agents use a Roth-Erev reinforcement learning algorithm to determine their bid and ask prices. The experimental design focuses on two treatment factors: market capacity; and a key Roth?Erev learning parameter that controls that degree of agent experimentation. For each capacity setting, it is shown that changes in the learning parameter have a substantial systematic effect on market efficiency.

Treasury Auctions, Uniform or Discriminatory?: An Agent-Based Approach

This study explores the use of the agent based computational economics (ACE) technique to address the question of how a Treasury should auction its securities. In particular, this study explores whether a Treasury should use a discriminatory-price rule. Buyers are modeled as profit seekers that are capable of submitting strategic bids via reinforcement learning. The buyers' profits are determined by auction prices and ex-post competitive resale prices. Experimental designs focus on four treatment varibles: (1) the buyers' learning representation; (2) market structures; (3) volatility of security prices in the secondary market; and (4) relative capacity (RCAP). Experimental findings show that security price volatility in the secondary market has little effect on market outcomes. However, market outcomes are sensitive to market structures, RCAP, and the buyers' learning representation. The two different auction rules result in different, persistent, systematically patterned market outcomes. Moreover, these findings help to explain why discrepancies have arisen among previous Treasury auction studies.agent-based computational economics; treasury auctions; discriminatory and unifome-price auction rules

Identifying the Entrepreneurship Characteristics of the Oil Palm Community Plantation Farmers in the Riau Area

Oil palm is an essential and strategic commodity in the Riau area because of its considerable role in supporting the peoples’ economy, especially for plantation farmers. Oil palm plantation activities have brought economic impacts to society there, both for the people who are directly involved with the plantations and for their surrounding communities. This regional advantage is a facility for farmers to be able to develop their farms as plantations. The aims of this research are to identify the entrepreneurship characteristics of the oil palm farmers, and also to identify the entrepreneurship characteristics that differentiate the farmers, as seen from their business’ achievements. The research used a grounded theory approach to identify the characteristics of oil palm farmers systematically. The sampling method used for the research was theoretical sampling, which is data gathering driven by the concepts derived from the theory of previous entrepreneurship characteristics studies. The research object is the oil palm farmers in Riau, Indonesia. The results of the analysis identified the entrepreneurship characteristics of the oil palm farmers, they are growth oriented, risk-taking, innovative, with a sense of personal control, self confident, and cooperative. But, among the characteristics, only the characteristic of their cooperation did not differentiate the oil palm farmers in the achievement of their business activities

MACROPRUDENTIAL STRESS-TESTING THE INDONESIAN BANKING SYSTEM USING THE CREDIT RISK MODEL

This study implements a macroprudential stress test and develops the Economic Risk Weighted-Capital Adequacy Ratio (ERW-CAR) to evaluate the resilience of the Indonesian banking sector. The results show that the historical and one-year ahead predicted ERW-CARs are currently three percent lower than the Indonesia regulatory CAR, and continue to decrease by nearly two percent following an exchange rate shock. However, the capital adequacy requirement stands above the eight percent threshold and the banks are still able to optimize their capital allocation.This study implements a macroprudential stress test and develops the Economic Risk Weighted-Capital Adequacy Ratio (ERW-CAR) to evaluate the resilience of the Indonesian banking sector. The results show that the historical and one-year ahead predicted ERW-CARs are currently three percent lower than the Indonesia regulatory CAR, and continue to decrease by nearly two percent following an exchange rate shock. However, the capital adequacy requirement stands above the eight percent threshold and the banks are still able to optimize their capital allocation

THE DETERMINANTS OF SYSTEMIC RISK: EVIDENCE FROM INDONESIAN COMMERCIAL BANKS

This paper examines the determinants of systemic risk across Indonesian commercial banks using quarterly data from 2001Q4 to 2017Q4. Employing four measures of systemic risk, namely value-at-risk (VaR), historical marginal expected shortfall (MESH), marginal expected shortfall from GARCH-DCC (MESdcc), and long-run marginal expected shortfall (LRMES), we find that bank size is positively related to systemic risk, whereas banks and economic loan activity are negatively related to systemic risk. These findings suggest that the government needs to regulate loan activities and to monitor big banks as they have significant impacts on bank systemic risk.This paper examines the determinants of systemic risk across Indonesian commercial banks using quarterly data from 2001Q4 to 2017Q4. Employing four measures of systemic risk, namely value-at-risk (VaR), historical marginal expected shortfall (MESH), marginal expected shortfall from GARCH-DCC (MESdcc), and long-run marginal expected shortfall (LRMES), we find that bank size is positively related to systemic risk, whereas banks and economic loan activity are negatively related to systemic risk. These findings suggest that the government needs to regulate loan activities and to monitor big banks as they have significant impacts on bank systemic risk