clptheory (version 0.1.0)

regtestrel: Regression-based Measures of Deviation.

Description

This function computes various regression based measures of deviation between the vector of all possible relative labor values and the vector of all possible relative prices of production. It runs a log-log and a level-level regression of relative prices on relative values and tests the joint null hypothesis that the intercept is 0 and the slope is 1.

Usage

regtestrel(x, y)

Value

A list with the following elements:

a0lg

Intercept in the log-log regression

a1lg

Slope in the log-log regression

r2lg

R-squared in the log-log regression

fstatlg

F-stat of the null hypothesis that a0=0 and a1=1 in the log-log regression

pvallg

P-value of the null hypothesis that a0=0 and a1=1 in the log-log regression

nlg

Number of observations in the log-log regression

a0lv

Intercept in the level-level regression

a1lv

Slope in the level-level regression

r2lv

R-squared in the level-level regression

fstatlv

F-stat of the null hypothesis that a0=0 and a1=1 in the level-level regression

pvallv

P-value of the null hypothesis that a0=0 and a1=1 in the level-level regression

nlv

Number of observations in the level-level regression

Arguments

x

price vector (1 x n).

y

value vector (1 x n).

References

Basu, Deepankar and Moraitis, Athanasios, "Alternative Approaches to Labor Values andPrices of Production: Theory and Evidence" (2023). Economics Department Working Paper Series. 347. URL: https://scholarworks.umass.edu/econ_workingpaper/347/

Examples

# Input-output matrix
A <- matrix(
data = c(0.265,0.968,0.00681,0.0121,0.391,0.0169,0.0408,0.808,0.165),
nrow=3, ncol=3, byrow = TRUE
)
# Direct labor input vector (complex)
l <- matrix(
data = c(0.193, 3.562, 0.616),
nrow=1
)
# Real wage bundle
b <- matrix(
data = c(0.0109, 0.0275, 0.296),
ncol=1
)
# Gross output vector
Q <- matrix(
data = c(26530, 18168, 73840),
ncol=1
)
# Direct labor input vector (simple)
l_simple <- l
# Market price vector
m <- matrix(data = c(4, 60, 7),nrow=1)
# Uniform nominal wage rate
wavg <- m%*%b
# Vector of nominal wage rates
w <- matrix(data=rep(wavg,3),nrow=1)
# Value of labor power
v <- 2/3
# Compute prices of production using NI
ni1 <- ppnewint1(A = A,l = l,w = wavg[1,1],v=v,Q = Q,l_simple = l)
# Regression-based measures of deviation
regtestrel(x=ni1$ppabs,y=ni1$lvalues)