make_pliv_CHS2015: Generates data from a partially linear IV regression model...
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make_pliv_CHS2015 R Documentation
Generates data from a partially linear IV regression model used in
Chernozhukov, Hansen and Spindler (2015).
Description
Generates data from a partially linear IV regression model used in
Chernozhukov, Hansen and Spindler (2015). The data generating process
is defined as
z_i = \Pi x_i + \zeta_i,
d_i = x_i'\gamma + z_i'\delta + u_i,
y_i = \alpha d_i + x_i'\beta + \epsilon_i,
with
\left(\begin{array}{c} \varepsilon_i \\ u_i \\ \zeta_i \\ x_i
\end{array} \right)
\sim \mathcal{N}\left(0,
\left(\begin{array}{cccc} 1 & 0.6 & 0 & 0 \\ 0.6 & 1 & 0 & 0
\\ 0 & 0 & 0.25 I_{p_n^z} & 0 \\ 0 & 0 & 0 & \Sigma \end{array}
\right) \right)
where \Sigma is a p_n^x \times p_n^x matrix with entries
\Sigma_{kj} = 0.5^{|j-k|} and
I_{p_n^z} is the p^z_n \times p^z_n
identity matrix. \beta=\gamma iis a p^x_n-vector with entries
\beta_j = \frac{1}{j^2}, \delta is a p^z_n-vector with
entries \delta_j = \frac{1}{j^2} and
\Pi = (I_{p_n^z}, O_{p_n^z \times (p_n^x - p_n^z)}).
Usage
make_pliv_CHS2015(
n_obs,
alpha = 1,
dim_x = 200,
dim_z = 150,
return_type = "DoubleMLData"
)
Arguments
n_obs
(integer(1))
The number of observations to simulate.
alpha
(numeric(1))
The value of the causal parameter.
dim_x
(integer(1))
The number of covariates.
dim_z
(integer(1))
The number of instruments.
return_type
(character(1))
If "DoubleMLData", returns a DoubleMLData object.
If "data.frame" returns a data.frame().
If "data.table" returns a data.table().
If "matrix" a named list() with entries X, y, d and
z is returned.
Every entry in the list is a matrix() object. Default is "DoubleMLData".
Value
A data object according to the choice of return_type.
References
Chernozhukov, V., Hansen, C. and Spindler, M. (2015),
Post-Selection and Post-Regularization Inference in Linear Models with
Many Controls and Instruments.
American Economic Review: Papers and Proceedings, 105 (5): 486-90.
DoubleML documentation built on June 22, 2024, 10:50 a.m.
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| make_pliv_CHS2015 | R Documentation |
Generates data from a partially linear IV regression model used in Chernozhukov, Hansen and Spindler (2015).
Description
Generates data from a partially linear IV regression model used in Chernozhukov, Hansen and Spindler (2015). The data generating process is defined as
z_i = \Pi x_i + \zeta_i,
d_i = x_i'\gamma + z_i'\delta + u_i,
y_i = \alpha d_i + x_i'\beta + \epsilon_i,
with
\left(\begin{array}{c} \varepsilon_i \\ u_i \\ \zeta_i \\ x_i
\end{array} \right)
\sim \mathcal{N}\left(0,
\left(\begin{array}{cccc} 1 & 0.6 & 0 & 0 \\ 0.6 & 1 & 0 & 0
\\ 0 & 0 & 0.25 I_{p_n^z} & 0 \\ 0 & 0 & 0 & \Sigma \end{array}
\right) \right)
where \Sigma is a p_n^x \times p_n^x matrix with entries
\Sigma_{kj} = 0.5^{|j-k|} and
I_{p_n^z} is the p^z_n \times p^z_n
identity matrix. \beta=\gamma iis a p^x_n-vector with entries
\beta_j = \frac{1}{j^2}, \delta is a p^z_n-vector with
entries \delta_j = \frac{1}{j^2} and
\Pi = (I_{p_n^z}, O_{p_n^z \times (p_n^x - p_n^z)}).
Usage
make_pliv_CHS2015(
n_obs,
alpha = 1,
dim_x = 200,
dim_z = 150,
return_type = "DoubleMLData"
)
Arguments
n_obs |
( |
alpha |
( |
dim_x |
( |
dim_z |
( |
return_type |
( |
Value
A data object according to the choice of return_type.
References
Chernozhukov, V., Hansen, C. and Spindler, M. (2015), Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments. American Economic Review: Papers and Proceedings, 105 (5): 486-90.
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