mostlyharmlesseconometrics.com valuation and analysis

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Title Mostly Harmless Econometrics
Description In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions — regression discontinuity designs and quantile regression
Keywords econometrics, statistics, book, MIT, regression discontinuity, standard errors, quantile regression, social science, methods, experimental, linear regression, statistical control, instrumental variables, analysis
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WebSite mostlyharmlesseconometrics faviconmostlyharmlesseconometrics.com
Host IP 67.20.113.35
Location United States
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mostlyharmlesseconometrics.com Valuation
US$6,301,036
Last updated: 2023-05-11 04:52:10

mostlyharmlesseconometrics.com has Semrush global rank of 1,679,772. mostlyharmlesseconometrics.com has an estimated worth of US$ 6,301,036, based on its estimated Ads revenue. mostlyharmlesseconometrics.com receives approximately 727,043 unique visitors each day. Its web server is located in United States, with IP address 67.20.113.35. According to SiteAdvisor, mostlyharmlesseconometrics.com is safe to visit.

Traffic & Worth Estimates
Purchase/Sale Value US$6,301,036
Daily Ads Revenue US$5,817
Monthly Ads Revenue US$174,491
Yearly Ads Revenue US$2,093,883
Daily Unique Visitors 48,470
Note: All traffic and earnings values are estimates.
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Mostly Harmless Econometrics Home Blog Ask a Question Send a Correction Post a Comment Table of Contents Authors Reviews Instructor’s Corner Store Home Questions about Questions (Chapter 1) The Experimental Ideal (Chapter 2) Making Regression Make Sense (Chapter 3) Instrumental Variables in Action: Sometimes You Get What You Need (Chapter 4) Parallel Worlds: Fixed Effects, Difference-in-differences, and Panel Data (Chapter 5) Getting a Little Jumpy: Regression Discontinuity Designs (Chapter 6) Quantile Regression (Chapter 7) Nonstandard Standard Error Issues (Chapter 8) DON’T PANIC! The core methods in today’s econometric toolkit are linear regression for statistical control, instrumental variables methods for the analysis of natural experiments, and differences-in-differences methods that exploit policy changes. In the modern experimentalist paradigm, these techniques answer clear causal questions such as: Do smaller classes increase learning? Do minimum wages reduce employment?
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