Macro¶
The Macro module contains classes that contain parameters common to all households, generate stochastic processes for returns and wages and other prices.
- class CPR.macro.CommonParameters(nsim, non_stochastic, extra_params)¶
This class sets and contains the parameters common to all households.
- Parameters
nsim (int) – number of simulations
non_stochastic (bool) – True if non stochastic simulation, False otherwise
extra_params (dict) – dictionary of extra parameters
- set_limits(name)¶
Set contributions limits for RRSP and TFSA.
- Parameters
name (str) – RRSP or TFSA
- prepare_ympe()¶
” Pre-reform ympe used to adjust DB benefits for CPP
- prepare_cpp()¶
Set percentages for cpp/qpp benefits.
- class CPR.macro.Prices(common, extra_params)¶
This class computes the times series for asset returns, interest rates on debt, deterministic wage profiles, housing price growth rate and price/rent ratio.
- Parameters
common (Common) – instance of the class Common
extra_params (dict) – dictionary of extra parameters
- simulate_ret(asset, common)¶
Simulate N series of length T nominal returns distributed lognormally with autocorrelation rho.
- Parameters
asset (str) – type of asset
common (Common) – instance of the class Common
- Returns
Array of nominal returns
- Return type
numpy.array
- compute_params_process(mu, rho, sigma)¶
Convert arithmetic mean mu and volatility sigma of the returns and autocorrelation rho of the log returns into \(\alpha\), \(\rho\) and \(\sigma_{\epsilon}\) of the process:
\(\ln(1+r_t) = \alpha + \rho * \ln(1+r_{t-1}) + \epsilon\), where \(\epsilon \sim N(0, \sigma_{\epsilon})\).
- Parameters
mu (float) – arithmetic mean
rho (float) – autocorrelation :math:
sigma (float) – standard deviation
- Returns
float – AR(1) coefficient (\(\alpha\))
float – Standard deviation of error term (\(\sigma_{\epsilon}\))
- simulate_housing(common)¶
Simulate series of nominal housing price growth (in \(\ln(1+r)\) form) and price-rent ratio.
- Parameters
common (Common) – instance of the class Common
- Returns
numpy.array – Array of nominal housing price growth
numpy.array – Array of price-rent ratios
- prepare_inflation_factors(common)¶
Compute inflation factors with base year 2018.
- Parameters
common (Common) – instance of the class Common
- Returns
Dictionary of inflation factors for each year
- Return type
dict
- simulate_interest_debt()¶
Creates N series of yearly nominal interest rate of length T for each type of debt
- Returns
Dictionary of interest rates by type of debt and year
- Return type
dict
- attach_diff_log_wages()¶
Creates a dictionary of differences in log wages by education and age.
- Returns
Dictionary of difference in log wages by education and age
- Return type
dict
- initialize_factors()¶
This function creates an instance of life.table by gender and province.
- Returns
dictionary of annuity factors by gender and provinces
- Return type
dict