diff --git a/ogcore/default_parameters.json b/ogcore/default_parameters.json
index a7d1bcce2..91aa1a18c 100644
--- a/ogcore/default_parameters.json
+++ b/ogcore/default_parameters.json
@@ -772,6 +772,25 @@
             }
         }
     },
+    "infra_investment_leakage_rate": {
+        "title": "Government infrastructure investment leakage rate",
+        "description": "Fraction of government infrastructure investment lost to leakage (e.g., corruption or other frictions) and treated as deadweight loss. Only (1 - infra_investment_leakage_rate) * I_g enters the public capital stock.",
+        "section_1": "Fiscal Policy Parameters",
+        "section_2": "Spending",
+        "notes": "A value of 0.0 (default) implies no leakage. A value of 0.2 implies 20% of infrastructure spending is lost before entering the public capital stock.",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
+    },
     "alpha_bs_T": {
         "title": "Proportional adjustment to government transfers relative to baseline amount when budget balance is true",
         "description": "Proportional adjustment to government transfers relative to baseline amount when budget balance is true. Set value for base year, click '+' to add value for next year.  All future years not specified are set to last value entered.",
diff --git a/ogcore/fiscal.py b/ogcore/fiscal.py
index 30bc2bdce..57ef29135 100644
--- a/ogcore/fiscal.py
+++ b/ogcore/fiscal.py
@@ -432,9 +432,13 @@ def get_K_g(K_g0, I_g, p, method):
     Law of motion for the government capital stock
 
     .. math::
-        K_{g,t+1} = \frac{(1 - \delta_g)K_{g,t} + I_{g,t}}
+        K_{g,t+1} = \frac{(1 - \delta_g)K_{g,t} + (1 - \phi_g)I_{g,t}}
             {(1 + \tilde{g}_{n,t+1})e^{g_y}}
 
+    where :math:`\phi_g` (``infra_investment_leakage_rate``) is the fraction
+    of infrastructure investment lost to leakage. When :math:`\phi_g = 0`,
+    there is no leakage and the formula reduces to the baseline.
+
     Args:
         K_g0 (scalar): initial stock of public capital
         I_g (array_like): government infrastructure investment
@@ -445,14 +449,17 @@ def get_K_g(K_g0, I_g, p, method):
         K_g (array_like): stock of public capital
 
     """
+    phi_g = p.infra_investment_leakage_rate
     if method == "TPI":
         K_g = np.zeros(p.T)
         K_g[0] = K_g0
         for t in range(p.T - 1):  # TODO: numba jit this
             growth = (1 + p.g_n[t + 1]) * np.exp(p.g_y)
-            K_g[t + 1] = ((1 - p.delta_g) * K_g[t] + I_g[t]) / growth
+            K_g[t + 1] = (
+                (1 - p.delta_g) * K_g[t] + (1 - phi_g) * I_g[t]
+            ) / growth
     else:  # SS
         growth = (1 + p.g_n_ss) * np.exp(p.g_y)
-        K_g = I_g / (growth - (1 - p.delta_g))
+        K_g = (1 - phi_g) * I_g / (growth - (1 - p.delta_g))
 
     return K_g
diff --git a/tests/test_fiscal.py b/tests/test_fiscal.py
index 5155bd857..07f8571f5 100644
--- a/tests/test_fiscal.py
+++ b/tests/test_fiscal.py
@@ -381,24 +381,26 @@ def test_get_I_g(baseline_spending, Ig_baseline, method):
 
 # need to parameterize to test for TPI and SS
 @pytest.mark.parametrize(
-    "K_g0,I_g,method,expected",
+    "K_g0,I_g,method,leakage,expected",
     [
-        (None, 0.2, "SS", 3.291689115882805),
+        (None, 0.2, "SS", 0.0, 3.291689115882805),
         (
             0.0,
             np.array([0.2, 0.3, 0.01]),
             "TPI",
+            0.0,
             np.array([0, 0.19028344, 0.46284331]),
         ),
+        (None, 0.2, "SS", 0.2, 2.6333513127062443),
     ],
-    ids=["SS", "TPI"],
+    ids=["SS", "TPI", "SS with leakage"],
 )
-def test_get_K_g(K_g0, I_g, method, expected):
+def test_get_K_g(K_g0, I_g, method, leakage, expected):
     """
     Test of the law of motion for the government capital stock
     """
     p = Specifications()
-    p.update_specifications({"T": 3})
+    p.update_specifications({"T": 3, "infra_investment_leakage_rate": leakage})
     p.g_n = np.array([0.02, 0.02, 0.02])
     p.g_n_ss = 0.01