L_hNV_rho

This function is used to estimate the parameters of the SSFA model where half-normal distribution of inefficiency term is assumed.

Spatial Stochastic Frontier Analysis (SSFA) is an original method for controlling the spatial heterogeneity in Stochastic Frontier Analysis (SFA) models, for cross-sectional data, by splitting the inefficiency term into three terms: the first one related to spatial peculiarities of the territory in which each single unit operates, the second one related to the specific production features and the third one representing the error term.

Elisa Fusco

ssfa

Spatial Stochastic Frontier Analysis

L_hNV_rho function

<dl> <dt>p</dt>
<dd>a vector with the parameters to be estimated.</dd> <dt>y</dt>
<dd>the dependent variable.</dd> <dt>X</dt>
<dd>the model matrix.</dd> <dt>sc</dt>
<dd>specifies the form of the frontier model (-1 = cost, 1 = production).</dd> <dt>w</dt>
<dd>the spatial weight matrix.</dd> <dt>sigmau2_sar</dt>
<dd>is the variance of the spatial correlated part of the inefficiency term estimated into <code>ssfa.fit</code> function.</dd></dl>

Arguments

SSFA half-normal log likelihood function — L_hNV_rho

<dl>

 <dt>p</dt>
<dd>a vector with the parameters to be estimated.</dd>

 <dt>y</dt>
<dd>the dependent variable.</dd>

 <dt>X</dt>
<dd>the model matrix.</dd>

 <dt>sc</dt>
<dd>specifies the form of the frontier model (-1 = cost, 1 = production).</dd>

 <dt>w</dt>
<dd>the spatial weight matrix.</dd>

 <dt>sigmau2_sar</dt>
<dd>is the variance of the spatial correlated part of the inefficiency term estimated into <code>ssfa.fit</code> function.</dd>

</dl>

L_hNV_rho: SSFA half-normal log likelihood function

Description

Usage

Value

Arguments

See Also