Labor calibration structure

[rickecon]

This issue lays out the structure of this calibration. The steady-state parameter section of the code in execute.py should have a parameter named calibrate_n. This parameter should be a boolean that equals True if you want to calibrate the S disutility of labor level parameters chi^n_s. Its value should be set to False if one does not want to estimate those parameters and just take them as exogenous inputs.

If calibrate_n = True, then the code must perform two steps.

1. Use the household Euler equations for labor supply to calculate chi^n_s_hat. Use CPS data for labor supply. @hayleefay and I wrote some nice code for this in the CPS_hrs_age repository. Get consumption data from the Consumer Expenditure Survey. The chi^n_s_hat values are related to the chi_n_s values in the model by the equation chi_n_s = (factor ** (sigma - 1)) * chi_n_s_hat.

2. Given the chi^n_s_hat values calculated from the Euler equations and a guess for the factor, we can solve the model. We solve for the factor by including it in the outer loop of the steady-state solution method with the interest rate r, such that factor = (data avg hh inc) / (model avg ss hh inc).

If calibrate_n = False, then solve the model with just r in the outer loop of the steady-state computation.

@SophiaMo