Merge pull request #1115 from Mv77/income_process

Use 1 point for degenerate income distributions
econ-ark · Feb 23, 2022 · 413e6d6 · 413e6d6
2 parents ea73795 + 731e9a9
commit 413e6d6
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diff --git a/Documentation/CHANGELOG.md b/Documentation/CHANGELOG.md
@@ -20,7 +20,7 @@ Release Date: TBD
 
 ### Minor Changes
 
-* Updates the lognormal-income-process constructor from `ConsIndShockModel.py` to use `IndexDistribution`. [#1024](https://github.com/econ-ark/HARK/pull/1024)
+* Updates the lognormal-income-process constructor from `ConsIndShockModel.py` to use `IndexDistribution`. [#1024](https://github.com/econ-ark/HARK/pull/1024), [#1115](https://github.com/econ-ark/HARK/pull/1115)
 * Allows for age-varying unemployment probabilities and replacement incomes with the lognormal income process constructor. [#1112](https://github.com/econ-ark/HARK/pull/1112)
 
 ### 0.12.0

diff --git a/HARK/ConsumptionSaving/ConsIndShockModel.py b/HARK/ConsumptionSaving/ConsIndShockModel.py
@@ -2790,7 +2790,9 @@ class LognormPermIncShk(DiscreteDistribution):
     def __init__(self, sigma, n_approx, neutral_measure=False, seed=0):
 
         # Construct an auxiliary discretized normal
-        logn_approx = MeanOneLogNormal(sigma).approx(n_approx, tail_N=0)
+        logn_approx = MeanOneLogNormal(sigma).approx(
+            n_approx if sigma > 0.0 else 1, tail_N=0
+        )
         # Change the pmf if necessary
         if neutral_measure:
             logn_approx.pmf = logn_approx.X * logn_approx.pmf
@@ -2825,8 +2827,10 @@ class MixtureTranIncShk(DiscreteDistribution):
 
     def __init__(self, sigma, UnempPrb, IncUnemp, n_approx, seed=0):
 
-        dstn_approx = MeanOneLogNormal(sigma).approx(n_approx, tail_N=0)
-        if UnempPrb > 0:
+        dstn_approx = MeanOneLogNormal(sigma).approx(
+            n_approx if sigma > 0.0 else 1, tail_N=0
+        )
+        if UnempPrb > 0.0:
             dstn_approx = add_discrete_outcome_constant_mean(
                 dstn_approx, p=UnempPrb, x=IncUnemp
             )