本博士論文係由三篇獨立論文組合而成，每篇論文都是透過超越對數
（Translog）生產 函數及隨機邊界法，對全世界各國進行經濟績效之評估。 第一 篇 名 為 「 Technical Efficiency of National Production under
Heterogeneous Technologies: A Latent Class Stochastic Frontier Approach」，研究對象為全世界人口較多、具代表性的三十個國家，期間涵 蓋1970年至2005 年，長達36年，總計 1,080 筆縱橫（Panel）資料。主要實 證結果顯示：採用潛在類別隨機邊界法，可將全世界各國區分為兩類不同技 術型態群組；其中，群組一是具競爭性的領導國家，群組二 則是落後的追隨 者。具競爭性的領導族群國家生產效率明顯高於落後的追隨國家，並且不論 是族群一或族群二國家的生產效率，都明顯高於採用一般傳統隨機生產邊界 模型 (例如 Battese and Coelli, 1992)的生產效率。顯然，可區別不同技術型 態的潛在類別 隨機邊界模型，有效將傳統單一技術類型隨機生產邊界模型中 歸於無效率項下的成分，成功篩出並歸於技術型態的不同，降低了模型誤差 並更準確的估計世界各國生產效率。 此外，兩個不同技術型態群組國家，不 論個別投入產出貢獻，或相乘項的投入產出貢獻 也都不相同；同樣的，兩個不 同技術型態群組國家，其決定生產效率的因素也大不相同。
第二篇篇名為「Efficiency Drivers of Nations: A Latent Class Stochastic Frontier Approach」，有別於前一篇運用教育和專利數做為區隔變數，本文係採用石油危機、金 融危機和通貨膨脹危機做為區隔變數。
第三篇 篇 名為「 Sources of East Asian Productivity Growth: A
Stochastic Frontier Analysis」，有別於前兩篇使用潛在類別隨機邊界模型， 本章節採用傳統隨機生產邊界模型(例如 Battese and Coelli, 1992)，在傳統的 生產要素勞動、資本、人力資本外， 同時導入十個影響國家生產的環境變數 探討東亞十國的生產效率和總要素生產力。結果 顯示， 東亞十國 的總要素 生 產率占 經 濟成長 率 的比重 頗 高，遠 高 於早 先「成長會計法 (growth accounting approach)」文獻。換言之，我們的結果顯示，東亞十國的經濟 成長並非來自要素累積，反而主要是來自總要素生產力的成長。整體總要素生 產力的來 源又以技術進步為大宗，技術效率反而成為拖累總要素成長的因素 之一。

The source of nation efficiency and Total Factor Productivity has begun to receive greater attention in academic circles and researchers started to discuss the factors that may influence the individual’s inefficiency and specified the inefficient term to be heterogeneous and affected by some exogenous variables.

In this dissertation, in order to detect efficiency drivers and incorporate exogenous variables, two type of heterogeneous technology model are utilizing. Not only the classical models, such as the Battese and Coelli (1992), but also the new developed models, such as the latent class stochastic frontier model are detected. In the first(chapter 2) and second (chapter 3) thesis, we apply recent advances of latent class stochastic frontier analysis in the world production frontier to examine levels of technical efficiency and efficiency drivers while in the chapter 4, the classical Battese and Coelli (1992,1995) models is utilizing to detect the sources of East Asian Productivity Growth.

This dissertation consists of three independent papers. Each of them utilizing different stochastic frontier analysis models explores technical efficiency of national  production under heterogeneous technologies.

The first paper is entitled “Technical Efficiency of National Production under Heterogeneous Technologies: A Latent Class Stochastic Frontier Approach” The production efficiency of the 30 most populous countries from 1970 to 2005 is analyzed using a latent class stochastic frontier model (LCSFM) that explicitly accounts for the difference in technological regimes. We find that the sample countries  can  be characterized by two distinct classes: “competitive leaders” and “pursuant stragglers”. Countries of the “competitive leaders” group experienced a higher technical efficiency than their pursuant stragglers counterparts, while using the traditional stochastic frontier
 
analysis results in lower-biased estimates on technical efficiency for both groups. Estimates on the translog production function suggest that inputs’ contributions to output and their interactions on affecting output vary between two classes.  Moreover, determinants of inefficiency also exhibit different influences between two classes.

The title of the second thesis is “Efficiency Drivers of Nations: A Latent Class Stochastic Frontier Approach”. Apart from the first paper incorporating oil crises, financial crises and hyperinflation crises, it instead, utilizes education and patents as separating variables.

The title of the third paper is “Sources of East Asian Productivity Growth: A Stochastic Frontier Analysis” In this study, we used the Stochastic Frontier approach to estimate and decompose Total Factor Productivity (TFP) growth in 10 East Asian countries. The result shows when output growth rates are compared, the general pattern observed indicates that the trend of TFP growth for East Asian countries is prominent and accounts for a larger proportion of output growth than most growth accounting approach estimated previously. In addition, the technical change (technological innovation) contributes considerably to TFP and economic growth in East Asian countries at the aggregate level. However, a poor record of efficiency has proven detrimental to enhancing productivity growth in East Asian countries.

Contents

Chapter 1 Introduction 	                                  1
Chapter 2 Technical Efficiency of National Production under Heterogeneous Technologies: A Latent Class Stochastic Frontier Approach 	                                  7
2.1	Introduction 	                                  9
2.2	Literature Review 	                         11
2.3	Methodology and Data 	                         13
2.4	Empirical Results 	                         19
2.5	Conclusions 	                                 24
Chapter 3 Efficiency Drivers of Nations: A Latent Class Stochastic Frontier Approach                             25
3.1	Introduction 	                                 28
3.2	Methodology and Data 	                         30
3.3	Empirical Results 	                         35
3.4	Conclusions 	                                 42
Chapter 4 Sources of East Asian Productivity Growth: A Stochastic Frontier Analysis                             43           
4.1	Introduction 	                                 46
4.2	TFP and Economic Performance in East Asia 	 49
4.3	Methodology and Data 	                         56
4.4	Empirical Results 	                         63
4.5	Conclusion 	                                 69
Chapter 5	Conclusions 	                         71
References 	                                         75
                  I
List of Tables
Table 2.1: Variable Definition, Basic Statistics, and Data Sources	87
Table 2.2: Characteristics of Two Classes	88
Table 2.3: Estimates of Production Frontier	89
Table 2.4: Estimated Technical Efficiency Scores	90
Appendix 2.1: Table Country List	91
Table 3.1: Descriptive Statistics	92
Table 3.2: Selection Statistics	93
Table 3.3: Characteristics of the Classes	94
Table 3.4: Summary Statistics of LCM	95
Table 3.5: Comparison of Efficiency Scores	96
Table 3.6: Efficiency Components	97
Table 3.7: Estimation Results	98
Table 3.7a: Estimation Results incorporating East Asian Dummy	99
Table 3.7b: Estimation Results with East Asian as Separating Variables	100
Table 3.8: Returns to Scale in the LCM	101
Table 3.9: Prior and Posterior Class Probabilities	102
Table 3.10:Assigning Class Membership	103
Appendix 3.1: Variable Sources and Definitions	104
Table 4.1: Descriptive Statistics for the Variables	106
Table 4.2: Maximum likelihood Estimates for SFA parameters	107
Table 4.3: Hypothesis testing for the adopted model	108
Table 4.4: Output Elasticities of the Input Factors and Technical Efficiency	109
Table 4.5: Source of the Growth of TFP by year	110
Table 4.6: Source of Growth in East Asian Countries and TFP Decomposition	111
Appendix 4.1: Variable Sources and Definitions	112
                    II

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