The operation of a political regime or a business entity involves the principal-agent problem. Checks and balances are the theme in the political arena, while management and controlling are the routine in the business world. To ensure that the ministers or the executive officers perform the desired functions, a monitoring scheme may be helpful. The crux of the issue is the lack of trust and information on those employed. Various effective monitoring networks, occidental or oriental, ancient or modern, military or civilian, have been deployed by numerous regimes and organizations to overcome the difficulties. The monitoring proceedings start from recruiting to remunerating and evaluating the workforce. To be sure, carrot and stick must be applied to achieve desirable results, besides enhancing the probability of detecting frauds. The merits of those networks seem to lie in commensurate rewarding and punishing of the personnel. Analyzing how those monitoring networks solved the controlling issue may give us insights into the critical incentive structures embodied. Moreover, the evolutionary path of institutions and organizations could be delineated via discerning the changes of those incentives, and vice versa.
Volume #10, Number #1
Published in June, 2006
When researchers analyze time series survey data, it is of importance to distinguish random sampling error from volatility of time varying. This study aims at introducing a statistical method of Samplemiser developed by U.S. politics scientists for distinguishing genuine movements in public opinion from random movements produced by sampling error. In this work, we first explain the applicability and importance of Samplemiser by a preliminary example. We then present the methodology of Samplemiser, the Kalman filtering and smoothing algorithm, and empirically apply this approach to the TVBS time series opinion survey data of Chen Shui Bian and Lien Chan in the 2004 Taiwan presidential election. The findings indicate that the smoothing algorithm reduces random sampling error in survey data, which implies that the data throughout the smoothing algorithm accurately gauge public opinion trends. The results also show that the estimates for autoregressive parameter (by which last period’s opinion affecting current opinion) influence the accuracy with which public opinion may be forecasted. We conclude that Samplemiser with the wed-based statistical software is an available and beneficial approach although it still has some limitations.
This study intends to explore the relationship between democratic administration and network governance, and to utilize “units of analysis” to compare and contrast the types of the implications of network governance in four countries including America, Britain, Germany, and the Netherlands. The main argument is that the theory of network governance may serve as a bridge between democracy and efficiency, which the field of public administration is in a dilemma as to pursue the both of goals in the same time. Moreover, reflections on both market failure and bureaucracy failure reveal that network theory, characterized as self-governance, resources interdependent, building trust and consensus, may become a useful conceptual framework of public governance under which government “co-steer” public policy along with other societal institutions. Nevertheless, as the modes of public governance evolve, each model of bureaucracy, market, and networks is one of institutions available for democratic administration, and none of which could be dominant in the society as a whole.
Survey research in Taiwan almost always focuses on studying public opinion in the national level. Due to the potential small n problem for less populous sub-geographic units, scholars have not utilized national survey data to estimate public opinions in any local level (e.g., county, town, or village). To overcome this sample size limitation, we use a method combining the multilevel modeling approach with the population information for post-stratification. We apply it to a set of pre-election national surveys of the 2004 Taiwan presidential election (sample size <2200) and produce county-level estimates of vote choice. Specifically, we first construct a multilevel logistic regression model to estimate the mean of the vote choice variable given demographics and county of residence. Second, we post-stratify on all the variables in the model by using the joint population distribution of the demographic variables within each county. Comparing our estimates with the actual county-level election outcomes, the average absolute error is less than 2 percentage points.
This paper tries to understand the role of judicial independent reform in the process of the breakdown of the Taiwanese clientelist system. The author argues that the decrease of coercion diminishes the ability of the authoritarian party to control and protect its brokers or local politicians. Democratization decreases the role of coercion in politics. The patrons cannot easily use coercion or the legal system to punish their brokers and clients any more after democratization. Without facing the threat of serious punishment, brokers and clients can easily defect from their patrons, challenge their authority, or demand more resources from their patrons. In the meantime, the patrons cannot easily use the judiciary to protect brokers’ and clients’ illegal activities. A more independent judiciary has had three effects politically on KMT clientelism. First, the KMT could not easily control and punish its maverick clientelist elites. Second, the corrupt clientelist elites’ prosecutions and subsequent verdicts caused the discontinuity of KMT local elites. Third, it became more difficult for the KMT to use a more independent judiciary to protect their clientelist elites’ vote-buying in elections. Without judicial protection, the KMT political machine could not function well.