計量經濟學

計量經濟學（英文：econometrics，其意思近似經濟測量）係經濟學同統計學嘅結合領域，旨在要諗點樣用統計學方法分析描述經濟現象嘅數據，籍此搵出唔同經濟現象之間嘅關係^[1]。技術化啲講，計量經濟學做嘅工作可以噉樣描述^[2]：計量經濟學，係對實際經濟現象嘅量化分析，基於同期嘅理論發展同埋觀察，而呢啲嘢係用適合嘅推論方法連繫埋一齊嘅。

計量經濟學會用好多推論統計技術：喺最基本上，計量經濟學用嘅技術學係迴歸模型；迴歸模型做嘅係攞一柞數據，數據入面有若干個個案，每個個案都喺 n 個變數 $\{x_{1},x_{2},...x_{n}\}$ 上有個值，迴歸分析會畫出一條線（迴歸模型），例如

x_{1}=\beta _{2}x_{2}+\beta _{3}x_{3}+...

，

表達呢柞變數之間嘅關係，而人攞住呢個噉嘅模型，將來就有得用個模型嚟做預測，例：用 $x_{2}$ 同 $x_{3}$ 嘅值估 $x_{1}$ 嘅值^[3]。除咗迴歸模型，計量經濟學研究仲可以用到結構方程模型等更加深嘅統計方法^[4]^[5]。

基礎概念

量度經濟

經濟學係社會科學下嘅領域，專門研究貨品同服務嘅生產、消費同埋分配：人有好多慾望，但係就算有咗現代科技，佢哋手頭上嘅資源－錢、時間、精神－都梗係有限嘅，佢哋成日都冇足夠嘅資源達到嗮佢哋想要達到嘅目的（稀缺性），例如一間公司唔夠資源生產嗮佢想要生產嘅嘢；因為資源有限，人喺做決策嗰陣往往需要做犧牲，需要放棄某啲嘢－呢啲取捨同資源分配嘅過程就係經濟學研究重心^[6]。

經濟學同第啲科學一樣，會要求研究者有方法客觀噉量度自己研究嘅現象同埋研究呢啲現象之間嘅關係。經濟指標泛指能夠反映經濟現象嘅指標數值。舉個例說明，本地生產總值（GDP）係經濟學成日研究嘅經濟指標：將某段時間之內經濟體裏面嘅最終貨品服務嘅市場價值冚唪唥加埋一齊，得出個數就係嗰個經濟體喺嗰段時間之內嘅 GDP；喺計 GDP 嘅過程之中，個分析者將個經濟體入面一大柞個體物件（貨品服務）嘅屬性（市場價值）以某啲方法結合埋做一個數值（就噉加埋一齊），用嚟反映經濟活動－呢啲價值會反映個經濟體總共生產咗幾多貨品服務^[7]。計量經濟學者跟住就會想用統計方法分析呢啲指標值之間嘅關係，從而理解經濟現象^[1]。

迴歸分析

迴歸分析可以話係計量經濟學嘅基礎。迴歸分析係一類嘅統計模型技術，指一啲用嚟建立描述兩個或者以上唔同變數之間嘅關係嘅數學模型^[8]。

喺統計學上，研究者好多時會想用一個變數嘅數值嚟預測第啲變數嘅數值；喺最簡單嗰種情況下，個統計模型會涉及兩個連續嘅變數，當中一個係自變數（IV）而另一個就係應變數（DV），而個研究者會用個 IV 嘅數值嚟預測個 DV 嘅數值；對個研究者嚟講，一個可能嘅做法係搜集啲數據返嚟，用啲數據做迴歸分析，整個模型（即係畫條線）出嚟，個模型就能夠幫佢預測

「當 IV 係呢個數值嗰陣，假設第啲因素不變，個 DV 嘅數值會傾向係幾多」^[9]^[10]。

估計理論

數據來源

分析方法

除咗迴歸模型之外，計量經濟學仲會用到好多統計方法，例子有格蘭傑因果。

應用例子

計量經濟學喺商學上相當有用：好似係管理學噉，管理學成日都會有興趣分析公司嘅表現－營業額、申請到嘅專利嘅數量... 等等－會點樣受到（例如）間公司嘅社會網絡影響，而呢種研究就會涉及分析政府數據庫當中有關唔同公司嘅營業額數據，用到計量經濟學方法^[11]^[12]。第啲商學領域上都會用到類似嘅方法做分析。

睇埋

參考

Giovannini, Enrico. Understanding Economic Statistics (PDF), OECD Publishing, 2008, ISBN 978-92-64-03312-2.

引咗

↑ ^1.0 ^1.1 Stock, J. H., and M. W. Watson. (2015). Introduction to Econometrics, Third Update, Global Edition. Pearson Education Limited.
↑ P. A. Samuelson, T. C. Koopmans, and J. R. N. Stone (1954). "Report of the Evaluative Committee for Econometrica." Econometrica, 22(2), p. 142，原版英文："... The quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference."
↑ Greene, William (2012). "Chapter 1: Econometrics". Econometric Analysis (7th ed.). Pearson Education. pp. 47–48. ISBN 9780273753568. Ultimately, all of these will require a common set of tools, including, for example, the multiple regression model, the use of moment conditions for estimation, instrumental variables (IV) and maximum likelihood estimation."
↑ Greene, William (2012). Econometric Analysis (7th ed.). Pearson Education. pp. 34, 41–42.
↑ Wooldridge, Jeffrey (2012). "Chapter 1: The Nature of Econometrics and Economic Data". Introductory Econometrics: A Modern Approach (5th ed.). South-Western Cengage Learning. p. 2.
↑ Krugman, Paul; Wells, Robin (2012). Economics (3rd ed.). Worth Publishers.
↑ Howitt, Peter M. (1987). "Macroeconomics: Relations with microeconomics". In Eatwell, John; Milgate, Murray; Newman, Peter. The New Palgrave Dictionary of Economics. The New Palgrave: A Dictionary of Economics (first ed.). pp. 273–276.
↑ Linear Regression with example 互聯網檔案館嘅歸檔，歸檔日期2020年3月27號，.. Towards Data Science.
↑ Seber, G. A., & Lee, A. J. (2012). Linear regression analysis (Vol. 329). John Wiley & Sons.
↑ YangJing Long (2009). "Human age estimation by metric learning for regression problems". Proc. International Conference on Computer Analysis of Images and Patterns: 74–82.
↑ Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study (PDF). Administrative science quarterly, 45(3), 425-455.
↑ Zaheer, A., & Soda, G. (2009). Network evolution: The origins of structural holes (PDF). Administrative Science Quarterly, 54(1), 1-31.

外拎

計量經濟學方面嘅學術期刊：

（英文）Journal of Financial Econometrics
（英文）The Econometrics Journal

[stock2015-1] 1.0 ^1.1 Stock, J. H., and M. W. Watson. (2015). Introduction to Econometrics, Third Update, Global Edition. Pearson Education Limited.

[samuelson54-2] P. A. Samuelson, T. C. Koopmans, and J. R. N. Stone (1954). "Report of the Evaluative Committee for Econometrica." Econometrica, 22(2), p. 142，原版英文："... The quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference."

[3] Greene, William (2012). "Chapter 1: Econometrics". Econometric Analysis (7th ed.). Pearson Education. pp. 47–48. ISBN 9780273753568. Ultimately, all of these will require a common set of tools, including, for example, the multiple regression model, the use of moment conditions for estimation, instrumental variables (IV) and maximum likelihood estimation."

[greene2012-4] Greene, William (2012). Econometric Analysis (7th ed.). Pearson Education. pp. 34, 41–42.

[5] Wooldridge, Jeffrey (2012). "Chapter 1: The Nature of Econometrics and Economic Data". Introductory Econometrics: A Modern Approach (5th ed.). South-Western Cengage Learning. p. 2.

[6] Krugman, Paul; Wells, Robin (2012). Economics (3rd ed.). Worth Publishers.

[howittmacro-7] Howitt, Peter M. (1987). "Macroeconomics: Relations with microeconomics". In Eatwell, John; Milgate, Murray; Newman, Peter. The New Palgrave Dictionary of Economics. The New Palgrave: A Dictionary of Economics (first ed.). pp. 273–276.

[datascienceregression-8] Linear Regression with example 互聯網檔案館嘅歸檔，歸檔日期2020年3月27號，.. Towards Data Science.

[9] Seber, G. A., & Lee, A. J. (2012). Linear regression analysis (Vol. 329). John Wiley & Sons.

[10] YangJing Long (2009). "Human age estimation by metric learning for regression problems". Proc. International Conference on Computer Analysis of Images and Patterns: 74–82.

[ahuja2000-11] Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study (PDF). Administrative science quarterly, 45(3), 425-455.

[12] Zaheer, A., & Soda, G. (2009). Network evolution: The origins of structural holes (PDF). Administrative Science Quarterly, 54(1), 1-31.

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