evaluate_my_model: Determine existence and uniqueness properties of the New...

In bfunovits/indeterminateR: Evaluates the Existence and Uniqueness Properties of LRE Models

Description

Function for evaluating the existence and uniqueness properties of a system in Sims' canonical form.

Usage

evaluate_my_model(deep_params = NULL, threshold = 1.01,
  my_model = "Lubik_Marzo_26_0", tol = sqrt(.Machine$double.eps),
  verbose = FALSE)

Arguments

deep_params	List object containing the deep parameters for the respective model. Default is the model by Lubik and Marzo (2007), equation (26) with i = 0. For more detail on the deep parameters see linear_parameters_LM_26_0.
threshold	Numeric value. Generalized eigenvalues larger than "threshold" are considered unstable.
my_model	String indicating which model should be evaluated. Default is the model by Lubik and Marzo (2007), equation (26) with i = 0.
tol	Threshold to determine what is considered practically zero. Default set to square root of machine precision.
verbose	Boolean variable to indicate whether matrices in Sims' canonical form, the QZ decomposition, and the matrices determining existence and uniqueness should be printed. Default is set to FALSE.

Value

Object of type "data_frame". Contains information about the existence and uniqueness properties. In particular, the variables are

• existence_boolean: TRUE if a stable and causal solution exists

• existence_dim_kernel: Dimension of the kernel of the matrix pertaining to the endogenous forecast errors in the existence condition.

• uniqueness_boolean: TRUE if the uniqueness condition is satisfied

• indeterminacy_dim: Dimension of indeterminacy as characterized in the paper accompanying this package

• indeterminacy_smallest_sv: Smallest singular value of the intersection of the spaces in the uniqueness condition. The smaller, the "more unique".

bfunovits/indeterminateR documentation built on May 28, 2019, 7:10 p.m.