Merge pull request #268 from alanlujan91/cycles_0

cycles = 0

macro/macro_parameters.py

@@ -0,0 +1,38 @@
+import numpy as np
+from HARK.ConsumptionSaving.ConsPortfolioModel import init_portfolio
+
+######################
+# Change Defaults    #
+######################
+
+sharkfin_portfolio = init_portfolio.copy()
+sharkfin_portfolio["cycles"] = 0  # 0 for infinite horizon
+sharkfin_portfolio["PermGroFac"] = [1.0]  # no drift in perm income
+sharkfin_portfolio["LivPrb"] = [1.0]  # no death
+sharkfin_portfolio["Rfree"] = 1.0  # risk free return, to focus on eq_prem
+sharkfin_portfolio["ex_post"] = None  # ex post parameters
+sharkfin_portfolio["UnempPrb"] = 0  # no unemployment
+
+######################
+# Annual Parameters  #
+######################
+
+annual_params = sharkfin_portfolio.copy()
+annual_params["CRRA"] = 5
+annual_params["DiscFac"] = 0.90
+annual_params["RiskyAvg"] = 1.05  # eq_prem is RiskyAvg - Rfree = 0.05
+annual_params["RiskyStd"] = 0.2  # standard deviation of risky returns
+annual_params["PermShkStd"] = [0.1]  # standard deviation of permanent shocks
+annual_params["TranShkStd"] = [0.1]  # standard deviation of transitory shocks
+
+######################
+# Quarterly Parameters  #
+######################
+
+quarterly_params = annual_params.copy()
+quarterly_params["DiscFac"] = annual_params["DiscFac"] ** (1 / 4)
+quarterly_params["RiskyAvg"] = annual_params["RiskyAvg"] ** (1 / 4)
+quarterly_params["RiskyStd"] = annual_params["RiskyStd"] / 2
+quarterly_params["PermShkStd"] = list(np.asarray(annual_params["PermShkStd"]) / 2)
+quarterly_params["TranShkStd"] = list(4 * np.asarray(annual_params["TranShkStd"]))
+quarterly_params["aXtraMax"] = 4 * annual_params["aXtraMax"]