(First-stage: tenure instrumented by age.)
* Example of reshaping wide data to long format reshape long gdp unemployment, i(country_id) j(year) Use code with caution. gdp and unemployment are the time-varying variables. i(country_id) specifies the unique entity identifier. j(year) creates a new variable indicating the time period. Declaring Panel Structure
is correlated with your independent variables, Pooled OLS estimates suffer from . stata panel data
It subtracts the time-series mean from each variable (within-transformation), effectively eliminating any time-invariant unobserved heterogeneity ( αialpha sub i
The null hypothesis is that the preferred model is Random Effects (RE). (First-stage: tenure instrumented by age
After declaring the panel, Stata will remember this structure. If you've previously set the data for time-series using tsset , xtset will recognize it.
isid idcode year, sort duplicates report idcode year duplicates drop idcode year, force // Use with caution j(year) creates a new variable indicating the time period
The standard Hausman test assumes homoscedasticity. If you have heteroscedasticity or serial correlation, the standard test is invalid. Install and use the user-written xtoverid command instead: ssc install xtoverid xtreg y x1 x2 x3, re xtoverid Use code with caution. 5. Addressing Panel Data Violations (Advanced Topics)
Stata will report if the panel is (same number of time points for all entities) or unbalanced . 4. Core Panel Commands Once set, you can use specialized xt commands :