Economic Questions and Data

Economic Questions  Economics suggests important relationships, often with policy implications, but virtually never suggests quantitative magnitudes of causal effects.

Examples of economic questions.  Does reducing class size improve elementary school education?  Is there racial discrimination in the market for home loans?  How much do cigarette taxes reduce smoking?  What will the rate of inflation be next year?

Q1: Reducing Class Size (Pros)  With fewer students in the classroom, each student gets more of the teacher’s attention, fewer class disruptions, and learning is enhanced and grades improve.  解決流浪教師

Q1: Reducing Class Size (Cons)  The observation does not seem to consistent with the actual data.  Maintaining a smaller class size costs more money.  根據教育部的資料， 93 學年度到 96 學年度，平均每年有 17 萬 169 名教師考績是甲等，約占 98.69% ，乙等和丙等都只 有一千多人，都不到 1% 。

Q2: Racial Discrimination  The law prohibit the US lending institution to take race into consideration when deciding to grant or deny a request of mortgage.  Researchers of Boston Fed found that 28% of black applicants are denied for mortgages while only 9% of whites applicants are denied.  Is there a racial discrimination?

Q3: Cigarette Tax  Many of the cost of smoking, such as the medical expenses of caring or the second hand smoking, are borne by the other members of society. Because of that, there is a role of government intervention.  Basic economics suggest that raising the cigarette tax is a way to limit its consumption. But how much? NT10, NT20, or NT150?  The answer depends on the price elasticity of smoking

Q4: Inflation  Forecasting the price level in the next year is in the interests of firms (investment decision), banks (mortgages rates), financial institutions (interest rates), and economists (jobs).  The price level is especially important for central banks because the size of inflation is the key reason to hike the primary interest rates.  It is very difficult to predict the price level of the next year.

This course is about how to use data to measure causal effects.  Ideally, we would like an experiment. class size; returns to education; cigarette prices;  But almost always we only have observational (nonexperimental) data.

Problems with observational data  Observational data poses major challenges: consider estimation of returns to education Possible Problems  confounding effects (omitted factors),  simultaneous causality,  correlation does not imply causality.

養雞生蛋或殺雞取卵： 論期交稅之降稅效果 連賢明 政大財政

動機和目的  研究動機：近年來政府實施一連串降稅政策，引發許多討 論，但彼此對降稅效果無共識，討論沒有交集。  本文目的：以 2006 年期交稅調降為例，分析降期交稅對台 灣股票指數期貨（簡稱台指期）交易量和稅收影響。

研究設計：  傳統估算：比較降稅前後交易量的變化 Q 台指期 （降稅後） - Q 台指期 （降稅前） 降稅時機可能是內生決定，造成估計上的偏誤  本研究採差異中的差異法估計降稅效果  DID 估算：以台指期為實驗組，摩台期為控制組 [Q 台指期 （降稅後） - Q 台指期 （降稅前） ]- [Q 摩台期 （降稅後） - Q 摩台期 （降稅前） ] 透過控制組的變化，排除外生環境影響

台指期月均量趨勢

台指期與摩台期月均量趨勢

 傳統方式高估降稅效果。 傳統估算：一年內交易量增加 26.7% DID 估算：一年內交易量增加 11.4%  降稅政策長期效果並沒有短期效果大。 傳統估算：兩年內交易量增加 30.2% DID 估算：兩年內交易量增加 4.9% 估計結果

In this course you will  Learn methods for estimating causal effects using observational data  Learn some tools that can be used for other purposes, for example forecasting using time series data;  Focus on applications – theory is used only as needed to understand the “why”s of the methods;  Learn to evaluate the regression analysis of others – this means you will be able to read/understand empirical economics papers in other econ courses;  Get some hands-on experience with regression analysis in your problem sets.

Data: Cross-Sectional Data  California School District Data

Data: Pooled Cross-Sectional Data  Can pool random cross sections and treat similar to a normal cross section. Will just need to account for time differences.

Data: Time Series Data CPI Inflation and Unemployment in the United States,

Data: Panel Data Cigaratte Sales, Prices, and Taxes by State and Year for U.S. States,