本文旨在量化廣告支出與總銷售額的線性關係，應用縱橫資料模型分析台灣產業從1993年到2013年之廣告銷售彈性。本文使用的樣本包含27種台灣各個不同的產業，分別估計各產業的廣告銷售彈性。研究結果顯示，在Pooled OLS模型估計之下的廣告銷售彈性為0.28，而使用縱橫資料的固定效果模型估計廣告銷售彈性得到的結果為0.26，最後改用動態的縱橫資料模型並以兩階段估計法做估計，得到短期的廣告銷售彈性為0.07，而長期的廣告銷售彈性為0.13。為觀察總體變數對銷售額的影響，加入總體變數進行估計，研究結果顯示，實質所得與銷售額呈現正向相關，實質產業價格與銷售額呈現負向相關。27個產業中，廣告支出占總銷售額的比率最高之兩產業分別為食品業及生物科技與醫療產業，比較其廣告銷售彈性以生技醫療產業為大。

The goal of this thesis is to explore quantification of a linear statistical relation between advertising and total sales. We apply pooled OLS regression and panel data analysis including fixed effects regression and dynamic panel data regression to estimate the advertising elasticity of sales for Taiwan industries from 1993 to 2013. This thesis contains 27 different industry and estimate the advertising elasticity of industry individually. We find the advertising elasticity is 0.28 by the pooled OLS model and the fixed effects panel model produces an estimate of 0.26. To estimate by dynamic panel data model, the short-term advertising elasticity is 0.07 and the long-term advertising elasticity is 0.13 using a two-step estimation method. From examination of the relative factors, we find the real income has a positive correlation with sales and the real industry price has a negative correlation with sales. Among the 27 industries, the highest industry of advertising expenditure to sales ratios is the bio-technology and medical care and food industries. With respect to the advertising elasticities of sales for these two industries, the bio-technology and medical care industry has a higher estimated elasticity than that of the food industry.

Table of Contents

List of Tables	II
List of Figures	III
I. Introduction 1
1.1 Statements of Research Topic and Overview 1
a. Advertising and the Concept of Elasticity 1
b. Historical Development and Current Scale of Advertising 5
1.2 Motivation and Goals of the Research 10
1.3 Methodology and Descriptive Statistics 14
1.4 Limitations and Recommendations of the Research 19
II. Literature Review 20
2.1 Chinese Literature 20
2.2 Western Literature 25
III. Theoretical Model 30
3.1 Advertising and Utility 30
3.2 Modeling the Advertising Behavior of a Firm 36
IV. Empirical Model and Analysis 43
4.1 An Empirical Model 43
4.2 Data Sources, Summary Statistics, and transformations 45
4.3 Estimation Results and Diagnostics 51
V. Conclusions and Recommendations 73
References 76
Appendix 1 79

List of Tables

Table 1-1 Total Media Advertisement Spending in Asia-Pacific, by Country, 2012-2018 9
Table 1-2 Numbers of Company in Each Industry 17
Table 2-1 Table of Chinese Literature Review in Chronological Order 22
Table 2-2 Table of Foreign Literature Review in Chronological Order 27
Table 4-1 Industry with Corresponding Industry Price 48
Table 4-2 Data Sources 49
Table 4-3 Descriptive Statistics 50
Table 4-4 Pooled OLS Regression 52
Table 4-5 Fixed Effects Panel Regression 54
Table 4-6 Dynamic Panel Regression 56
Table 4-7 The Advertising Elasticities of Each Industry with Pooled OLS Regression and Fixed Effects Panel Regression 60
Table 4-8 The Advertising Elasticities of Each Industry with Dynamic Panel Regression 62
Table 4-9 Twenty-Seven Industries with Advertising Expenditure to Sales Ratios 64
Table 4-10 Summary Statistics of Each Industry Advertising Elasticities with Pooled OLS and Fixed Effects Panel Regression 68
Table 4-11 Summary Statistics of Each Industry Advertising Elasticities with Dynamic Panel Regression 69
Table 4-12 Pooled OLS and Panel Data Regression with Adding Macroeconomic Variables 72
 
List of Figures

Figure 1-1 Total Media Advertisement Spending Worldwide, 2012-2018 8
Figure 3-1  The Advertising that Leads to the Shifting of Demand and Increased Sales 38
Figure 4-1 Twenty-Seven Industries with Advertising Expenditure to Sales Ratios 65

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