Description Usage Arguments Value
Basic computing engine to calculate confidence intervals and pvalues in
shiftshare designs using different inference methods, as specified by
method
.
1 2 3 4 5 6 7 8 9 10 11 12  reg_ss.fit(
y,
X,
W,
Z,
w = NULL,
method = c("akm", "akm0"),
beta0 = 0,
alpha = 0.05,
region_cvar = NULL,
sector_cvar = NULL
)

y 
Outcome variable, vector of length 
X 
Shiftshare 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 pvalues) 
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 pvalues 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(1alpha/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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