教授给我的评价原文大概是:. 1point 3 acres
"If you are a bad writer, people will believe you are a bad thinker--muddled words are the surest sign of muddled thoughts. You tend to add longer and more exotic words until your idea is lost and you ultimately write something that is false or unsubstantiated. It leads me to believe you want to distract rather than illuminate. "
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我写的是对一篇关于IV(instrumental variable)的经济论文的review。我就摘两段自认为问题所在的段落,这两段是在说明为什么此论文的研究不能使用ols模型进行估计。如果哪位大神可以指点迷津,我不胜感激啊。
“Initially if we measure the veteran impact on income using OLS model, the
independent variable would be a binary variable: "whether the person i is a veteran
at time t in cohort c" and the dependent variable would be the person’s
income. Control variables in the model should include all the variables that
affect a person’s income, but are uncorrelated with the independent variable. In
addition, the cohort effect dummy variable and period effect dummy variable
should both exist in the model.
However, a self-selection issue occurs when certain unobservable variables which
also affect the binary veteran variable fail to be included in the model. Perhaps
people who would gain most benefits from military (they might obtain promises
to get high income as a veteran) choose to join the Vietnam War. Or their decision
to fight in the war is correlated with other characteristics that affect earnings.
For example, people (even from a poor family) with less IQ or ability might have
higher possibility to join the war if their parents believe they will earn more than
not being veterans. These joining-war decisions and the get-most-benefit situation
end up contained in the error term since they are hardly measurable to
be control variables. Due to the correlation with unobservable control variables,
the independent variable turns out to be endogenous. In addition, the veteran
impact on income may be overestimated since the research subjects are veterans
who have ensured higher income; or the model might underestimate the veteran.google и
impact: Some veterans with less IQ or ability will earn even less than common
veterans because of the lacking of several-years’ education and working experience.”
“The author applies the instrumental variable approach to solve the identification
problem. He selects the draft lottery for the Vietnam War as the binary
veteran variable’s instrument variable. The number of draft lotteries people. Waral dи,
draw in each year and each cohort determines whether they are chosen to join
the Vietnam War. Since the lottery numbers are drafted randomly to registered
people (so-called Random Sequence Number (RSN)), the draft lottery being as an-baidu 1point3acres
exogenous variable and is independent with error term seems plausible. As the requirement
states that people with draft lottery RSN below a ceiling (determined
by the Defense Department) are selected to join the war, this implies a correlation
between the draft lottery and veteran explanatory variable. In conclusion, the draft
lottery is considered to be an instrument variable. while being uncorrelated
with the error term in the model, it is correlated with the endogenous explanatory
variable and indirectly affects the dependent variable income. By replacing the
veteran explanatory variable in the OLS model with another estimation model of. 1point 3acres
veterans with the draft lottery as an independent variable, the new model then becomes
a good estimation model (meets all Gauss Assumption: BLUE, unbiased and
efficient).”