gnriv: Estimate fixed input elasticity and total productivity:...

In davidjin0/gnrprod: Estimates Gross Output Functions

Estimate fixed input elasticity and total productivity: Gandhi, Navarro, Rivers (GNR) lags as instruments; second stage

Description

The gnriv function implements the second stage of the GNR production function estimation routine, nonparametrically identifying the fixed input elasticities of the production function and total productivity. This function accepts an object of class 'gnrflex'. The parameters are optimized using the function optim.

For details, see Gandhi, Navarro, and Rivers (2020).

Usage

gnriv(object, control, ...)

Arguments

object	object of class 'gnrflex'.
control	an optional list of convergence settings. See gnriv.control for listing.
...	additional optional arguments passed to optim.

Value

a list of class 'gnriv' containing three elements:

fixed_elas: a numeric matrix of estimated elasticities of fixed inputs for each observation.

productivity: a numeric vector of estimated total productivity.

control: the list of convergence control parameters. See gnriv.control for available parameters.

References

Gandhi, Amit, Salvador Navarro, and David Rivers. 2020. "On the Identification of Gross Output Production Functions." Journal of Political Economy, 128(8): 2973-3016. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1086/707736")}.

Examples

require(gnrprod)
data <- colombian
industry_311_flex <- gnrflex(output = "RGO", fixed = c("L", "K"),
                             flex = "RI", share = "share", id = "id",
                             time = "year", data = data,
                             control = list(degree_w = 2, maxit = 200))

industry_311_fixed <- gnriv(industry_311_flex,
                            control = list(trace = 1))

davidjin0/gnrprod documentation built on July 2, 2023, 10:38 p.m.