scholarly journals Optimal Incentives in a Principal–Agent Model with Endogenous Technology

Games ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 6
Author(s):  
Marco Marini ◽  
Paolo Polidori ◽  
Désirée Teobaldelli ◽  
Davide Ticchi
Keyword(s):  
Principal Agent ◽  
Agent Model ◽  
Principal Agent Model ◽  
Optimal Incentives ◽  
Endogenous Technology

Why Were Workers Whipped? Pain in a Principal-Agent Model

1990 ◽  
Vol 100 (403) ◽  
pp. 1109 ◽  
Author(s):  
Michael Suk-Young Chwe
Keyword(s):  
Principal Agent ◽  
Agent Model ◽  
Principal Agent Model

scholarly journals Does Fiscal Decentralization in Indonesia have Asymmetrical Information?: Principal-Agent Model, Primal-Dual, and a Neural Network Analysis

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Kun Haribowo
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Central Government ◽  
Fiscal Decentralization ◽  
Principal Agent ◽  
Agent Model ◽  
Primal Dual ◽  
Principal Agent Model ◽  
Artificial Neural ◽  
Subnational Governments

In reality, subnational governments suffer from moral hazard, creating uncertainty which, in turn, causes economic inefficiency. The behavior of subnational governments cannot be observed by the central government. An analysis which takes into account this phenomenon is therefore needed. Decentralization implies delegating authority from central government to subnational governments. In this study, the subnational government is represented by the local government. This study utilizes a model of principal-agent. The central government acts as a principal who delegates fiscal authority to subnational governments who act as agents. By applying principal-agent model, we can use the primal-dual approach to analyze both revenue and expenditure assignment associated with the tax effort of the subnational governments. The result from artificial neural network approach shows that asymmetric information between central and subnational governments exists in Indonesia.Keywords: Artificial Neural Network, Fiscal Decentralization, Local Tax Effort, Primal-Dual, Principal-Agent.

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