regtestrel | R Documentation |

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.

```
regtestrel(x, y)
```

`x` |
price vector (1 x n). |

`y` |
value vector (1 x n). |

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 |

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/

```
# 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)
```

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