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《计量经济学》课程教学资源(PPT课件讲稿,英文版)ch19 Summary and conclusions

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Choosing a Topic Start with a general area or set of questions Make sure you are interested in the topic Use on-line services such as EconLit to investigate past work on this topic Narrow down your topic to a specific question or issue to be investigated Work through the theoretical issue Economics 20-Prof. Anderson
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Summary and conclusions Carrying Out an Empirical Project Economics 20- Prof anderson

Economics 20 - Prof. Anderson 1 Summary and Conclusions Carrying Out an Empirical Project

Choosing a topic o Start with a general area or set of questions o Make sure you are interested in the topic o Use on-line services such as econLit to investigate past work on this topic e Narrow down your topic to a specific question or issue to be investigated o Work through the theoretical issue Economics 20- Prof anderson

Economics 20 - Prof. Anderson 2 Choosing a Topic Start with a general area or set of questions Make sure you are interested in the topic Use on-line services such as EconLit to investigate past work on this topic Narrow down your topic to a specific question or issue to be investigated Work through the theoretical issue

Choosing data Want data that includes measures of the things that your theoretical model imply are mportant o Investigate what type of data sets have been used in the past literature Search for what other data sets are available(for example, ICPSR) e Consider collecting your own data Economics 20- Prof anderson

Economics 20 - Prof. Anderson 3 Choosing Data Want data that includes measures of the things that your theoretical model imply are important Investigate what type of data sets have been used in the past literature Search for what other data sets are available (for example, ICPSR) Consider collecting your own data

Using the data o Create variables appropriate for analysis e For example, create dummy variables from categorical variables, create hourly wages etc o Check the data for missing values, errors outliers. etc Recode as necessary, be sure to report what you did Economics 20- Prof anderson 4

Economics 20 - Prof. Anderson 4 Using the Data Create variables appropriate for analysis For example, create dummy variables from categorical variables, create hourly wages, etc. Check the data for missing values, errors, outliers, etc. Recode as necessary, be sure to report what you did

Estimating a model o Start with a model that is clearly based in theory o Test for significance of other variables that are theoretically less clear o Test for functional form misspecification Consider reasonable interactions quadratics, logs, etc. Economics 20- Prof anderson 5

Economics 20 - Prof. Anderson 5 Estimating a Model Start with a model that is clearly based in theory Test for significance of other variables that are theoretically less clear Test for functional form misspecification Consider reasonable interactions, quadratics, logs, etc

Estimating a Model (continued) o Dont lose sight of theory and the ceteris paribus interpretation- you need to be careful about including variables that a greatly alter the interpretation For example, effect of bedrooms conditional on square footage e Be careful about putting functions of y on the right hand side- affects interpretation Economics 20- Prof anderson 6

Economics 20 - Prof. Anderson 6 Estimating a Model (continued) Don’t lose sight of theory and the ceteris paribusinterpretation – you need to be careful about including variables that greatly alter the interpretation For example, effect of bedrooms conditional on square footage Be careful about putting functions of y on the right hand side – affects interpretation

Estimating a Model (continued) e Once you have a well-specified model, need to worry about the standard errors Test for heteroskedasticity ◆ Correct if necessary Test for serial correlation if there is a time component ◆ Correct if necessary Economics 20- Prof anderson 7

Economics 20 - Prof. Anderson 7 Estimating a Model (continued) Once you have a well-specified model, need to worry about the standard errors Test for heteroskedasticity Correct if necessary Test for serial correlation if there is a time component Correct if necessary

Other problems o Often you have to worry about endogeneity of the key explanatory variable Endogeneity could arise from omitted variables that are not observed in the data o Endogeneity could arise because the model Is really part of a simultaneous equation Endogeneity could arise due to measurement error Economics 20- Prof anderson 8

Economics 20 - Prof. Anderson 8 Other Problems Often you have to worry about endogeneity of the key explanatory variable Endogeneity could arise from omitted variables that are not observed in the data Endogeneity could arise because the model is really part of a simultaneous equation Endogeneity could arise due to measurement error

k Other Problems( continued) o If you have panel data, can consider a fixed effects model(or first differences) e Problem with FE is that need good variation over time o Can instead try to find a perfect instrument and perform 2SLS Problem with Iv is finding a good instrument Economics 20- Prof anderson 9

Economics 20 - Prof. Anderson 9 Other Problems (continued) If you have panel data, can consider a fixed effects model (or first differences) Problem with FE is that need good variation over time Can instead try to find a perfect instrument and perform 2SLS Problem with IV is finding a good instrument

Interpreting your results o Keep theory in mind when interpreting results o Be careful to keep ceteris paribus in mind e Keep in mind potential problems with your estimates- be cautious drawing conclusions o Can get an idea of the direction of bias due to omitted variables measurement error or simultaneity Economics 20- Prof anderson 10

Economics 20 - Prof. Anderson 10 Interpreting Your Results Keep theory in mind when interpreting results Be careful to keep ceteris paribus in mind Keep in mind potential problems with your estimates – be cautious drawing conclusions Can get an idea of the direction of bias due to omitted variables, measurement error or simultaneity

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