Large-N observatio ional l data 1 Large-N observational data The - PowerPoint PPT Presentation

Large-N observatio ional l data 1

Large-N observational data The basic idea • Whenever cases are non-experimental and one wants to analyze several of them, researcher has to revert to statistical methods to control for confounding variables. • Association between variables can be established visually (i.e., through scatterplots) and captured as minimizing sum of the squared distances (OLS regression) • You need to do the best you can to control for major alternative hypotheses. Common pitfalls • Endogeneity • LOVB • Measurement error (and crappy data) • Non-comparable data (e.g., urbanization) • Causal heterogeneity Observational data very useful in disconfirming contentions, as correlation is commonly a requisite for causal relationship 2

Omitted variable bias and endogeneity + Effect of X upon Y X Y appears stronger 0 than it is + X Y 0 + X Y Effect of X upon Y + appears stronger Q + than it is; no actual effect of X on Y + True effect of X on Y X Y More complex forms washes out in the - analysis; there Q Z Z² Z³ appears to be no effect when there actually it one X Y ? 3

Omitted variable bias can inflate coefficients An example Education Annual income If education and parents’ Parents’ SES SES are correlated, then… Apparent effect of education Cell entries represent on income fortnightly income in $K 3 3 4 5 3 True $ effect of Education 2 education 2 3 4 tier 2 1 1 2 3 1 1 2 3 0 1 2 3 Parents’ SES Education 4

People use the term “measurement error” to refer to at least two different things Valid but not reliable Reliable but not valid (inefficient/imprecise) Example? Example? 5

Inefficient measures have different effects Random error on DV Random error on IV True e.g., corruption Apparent e.g.: British colonial legacy e.g., British colonial legacy Note that, in the MV case, measurement error can bias coefficients in unpredictable ways 6

Galton’s coefficient of regression (and the concept of “regression toward the mean”) Son’s height Father’s height 7

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