ivreg_ss.fit | R Documentation |
Basic computing engine to calculate confidence intervals and p-values in an
instrumental variables regression with a shift-share instrument, using
different inference methods, as specified by method
.
ivreg_ss.fit( y1, y2, X, W, Z, w = NULL, method = c("akm", "akm0"), beta0 = 0, alpha = 0.05, region_cvar = NULL, sector_cvar = NULL )
y1 |
Outcome variable. A vector of length |
y2 |
Endogenous variable, vector of length |
X |
Shift-share vector with length |
W |
A matrix of sector shares, so that |
Z |
Matrix of regional controls, matrix with |
w |
vector of weights (length |
method |
Vector specifying which inference methods to use. The vector elements have to be one or more of the following strings:
|
beta0 |
null that is tested (only affects reported p-values) |
alpha |
Determines confidence level of reported confidence intervals,
which will have coverage |
region_cvar |
A vector with length |
sector_cvar |
A vector with length |
Returns an object of class "SSResults"
containing the
estimation and inference results. The print
function can be used
to print a summary of the results. The object is a list with at least the
following components:
Point estimate of the effect of interest beta
A vector of standard errors and a vector of p-values of the null
H_0 : beta = beta0 for the inference
methods in method
, with beta0 specified by the
argument beta0
. For the method "akm0"
, the standard error
corresponds to the effective standard error (length of the confidence
interval divided by 2*stats::qnorm(1-alpha/2)
)
Upper and lower endpoints of the confidence interval for
the effect of interest beta, for each of the methods in
method
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