# regression) post-estimation command. Estimate model 1, then model 2, and it forms the seemingly unrelated variance-covariance matrix (estimates) for the combined set of coefficients. With that, you can test if some coefficient from model 1 is equal to some coefficient from model 2. An example from panel data for the impact of variable growst (state economic growth) on variable low25 (percentage of income going to the poorest 25% of tax units over the 1913-1978 period vs. the 1979-2003 period for an ECM model (i.e., first differenced dependent variable with a lagged value of the dependent variable as an independent variable: (1) tsset stnum year, yearly; (2) run:

# reg d.low25 l.low25 d.growst l.growst if year<1979

estimates store low25early

reg d.low25 l.low25 d.growst l.growst if year>1978

estimates store low25late

suest low25early low25late, vce (cluster stnum)

test [low25early_mean=low25late_mean]

test [low25early_mean]d.growst=[low25late_mean]d.growst

test [low25early_mean]l.growst=[low25late_mean]l.growst

# You need to run a separate test for each independent variable. If you are using differenced and lagged values of a variable as an independent variable you would need two tests per variable (i.e., the differenced version of the variable is one variable and the lagged version of the same variable is a second variable).

# Standardized Coefficients: in regression just add ,beta to the end of the

# command line – thus: regress tax cons party stinc, beta

# To obtain standardized coefficients for probit, logit and multinomial logit

first estimate the desired equation. After the results appear type the following in the command line: listcoef (You may need to download this option from Stata - it will work but may not be built into the package – to download you need to be connected to the internet and type the following in the command line: ssc install listcoef – if that doesn’t work try findit listcoef - then you need click on the appropriate link). If you are interested in the relative value of coefficients, use the coefficients in the “bStdXY” (i.e., the coefficients in this column should be identical to what you receive with the “beta” command in regression). Additionally, two bStdXY coefficients have virtually the same ratio as do the same two bStdX coefficients).

# Marginal Effects: run regress, probit or logit. Then in command line type: mfx

# In probit you can also get the marginal effects of each independent variable by replacing probit with dprobit

Comparing Models in Probit/Logit (i.e., nesting – like F test in regression

for the equality of two R squareds) – from page 144 of J. Scott Long and Jeremy Freese, Regression Models for Categorical Dependent Variables Using Stata, 2nd. ed. –

probit involvem repcont demcont ablegal fund1 catholic

estimates store fullmodel