choose_bandwidth_and_estim_condl_proba: This function chooses the bandwidths to be used for the...

In cgaillac/MarginalFElogit: Estimation of Average Marginal Effects in Fixed Effect Logit Models

This function chooses the bandwidths to be used for the estimation through local linear regressions of the conditional distribution of S, as described in online appendix B of the DDL paper. It then proceeds to estimate these conditional probabilities, and saves them in estimators.

Description

This function chooses the bandwidths to be used for the estimation through local linear regressions of the conditional distribution of S, as described in online appendix B of the DDL paper. It then proceeds to estimate these conditional probabilities, and saves them in estimators.

Usage

choose_bandwidth_and_estim_condl_proba(data, estimators)

Arguments

data

is an environment variable containing the relevant data, formatted by format_data (see function documentation): - data$Y a matrix of size n x Tmax containing the values of the dependent variable Y. - data$X an array of size n x Tmax x dimX containing the values of the covariates X. - data$clusterIndexes a vector of size n containing the index of the cluster each observation belongs to. The computed asymptotic variance is clustered.

estimators

is an environment variable containing the results from logit and FE logit estimation: - estimators$beta_hat$beta_hat is the CMLE estimate of the FE logit slope parameter. - estimators$alphaFElogit is the estimate of the constant parameter in a standard logit model using the estimated CMLE slope parameter. If empty, it is estimated.

Value

The function does not return anything, but the estimators environment has the following parameters added: - estimators$h_local_lin_proba a vector of length (Tmax + 1) containing, in j-th position, the bandwidth used to estimate the P(S = j - 1 | X)'s. - estimators$condlProbas: a matrix of size n x (Tmax + 1) containing, in position (i, j), the estimate for P(S = j - 1 | X) at the i-th observation. - estimators$densityEstimate: a matrix of size n x (Tmax + 1) containing, at each row (individual), the estimated density for having covariates (X_1, ..., X_T). Each column represents the value found using the corresponding bandwidths from h.

cgaillac/MarginalFElogit documentation built on Dec. 24, 2024, 3:23 p.m.