Parameter values are stored as attributes of the ConsumerType the values are used for. For example, the risk-free interest rate Rfree is stored as BaselineExample.Rfree. Because we created BaselineExample using the default parameters values. at the moment BaselineExample.Rfree is set to the default value of Rfree (which, at the time this demo was written, was 1.03). Therefore, to change the risk-free interest rate used in BaselineExample to (say) 1.02, all we need to do is: BaselineExample.Rfree = 1.02 """ ## Change some parameter values BaselineExample.Rfree = 1.02 # change the risk-free interest rate BaselineExample.CRRA = 2.0 # change the coefficient of relative risk aversion BaselineExample.BoroCnstArt = -0.3 # change the artificial borrowing constraint BaselineExample.DiscFac = 0.5 # chosen so that target debt-to-permanent-income_ratio is about .1 # i.e. BaselineExample.solution[0].cFunc(.9) ROUGHLY = 1. ## There is one more parameter value we need to change. This one is more complicated than the rest. ## We could solve the problem for a consumer with an infinite horizon of periods that (ex-ante) ## are all identical. We could also solve the problem for a consumer with a fininite lifecycle, ## or for a consumer who faces an infinite horizon of periods that cycle (e.g., a ski instructor ## facing an infinite series of winters, with lots of income, and summers, with very little income.) ## The way to differentiate is through the "cycles" attribute, which indicates how often the ## sequence of periods needs to be solved. The default value is 1, for a consumer with a finite ## lifecycle that is only experienced 1 time. A consumer who lived that life twice in a row, and ## then died, would have cycles = 2. But neither is what we want. Here, we need to set cycles = 0, ## to tell HARK that we are solving the model for an infinite horizon consumer. ## Note that another complication with the cycles attribute is that it does not come from
Parameter values are stored as attributes of the ConsumerType the values are used for.
For example, the risk-free interest rate Rfree is stored as BaselineExample.Rfree.
Because we created BaselineExample using the default parameters values.
at the moment BaselineExample.Rfree is set to the default value of Rfree (which, at the time
this demo was written, was 1.03). Therefore, to change the risk-free interest rate used in
BaselineExample to (say) 1.02, all we need to do is:
BaselineExample.Rfree = 1.02
"""
## Change some parameter values
BaselineExample.Rfree = 1.02 #change the risk-free interest rate
BaselineExample.CRRA = 2. # change the coefficient of relative risk aversion
BaselineExample.BoroCnstArt = -.3 # change the artificial borrowing constraint
BaselineExample.DiscFac = .5 #chosen so that target debt-to-permanent-income_ratio is about .1
# i.e. BaselineExample.solution[0].cFunc(.9) ROUGHLY = 1.
## There is one more parameter value we need to change. This one is more complicated than the rest.
## We could solve the problem for a consumer with an infinite horizon of periods that (ex-ante)
## are all identical. We could also solve the problem for a consumer with a fininite lifecycle,
## or for a consumer who faces an infinite horizon of periods that cycle (e.g., a ski instructor
## facing an infinite series of winters, with lots of income, and summers, with very little income.)
## The way to differentiate is through the "cycles" attribute, which indicates how often the
## sequence of periods needs to be solved. The default value is 1, for a consumer with a finite
## lifecycle that is only experienced 1 time. A consumer who lived that life twice in a row, and
## then died, would have cycles = 2. But neither is what we want. Here, we need to set cycles = 0,
## to tell HARK that we are solving the model for an infinite horizon consumer.
## Note that another complication with the cycles attribute is that it does not come from
