cagr revenues functionality

app.py

@@ -33,14 +33,15 @@ print(data)
 
 # %%
 baseline_interest_rate = 3.67
-baseline_revenues = 15928.73
+#baseline_revenues = 15928.73
+baseline_cagr_revenues = 4.02
 
-def plot_interest_coverage(interest_rate, revenues):
+def plot_interest_coverage(interest_rate, cagr_revenues):
 
     # calculate the yearly increase in the interest rate based on the projected interest rate in 2054
     interest_rate_yearly_increase = (interest_rate - baseline_interest_rate) / (2054 - 2025) / 100
     # calculate the yearly increase in revenues based on the projected interest rate in 2054
-    revenues_yearly_increase = (revenues - baseline_revenues) / (2054 - 2025)
+    # revenues_yearly_increase = (revenues - baseline_revenues) / (2054 - 2025)
 
     # add a baseline net interest / revenues column
     data["Net Interest / Revenues (Baseline)"] = data["Net Interest"] / data["Total Revenues"]
@@ -48,33 +49,37 @@ def plot_interest_coverage(interest_rate, revenues):
     # add a baseline net interest / revenues ex SS OASDI column
     data["Net Interest / Revenues ex SS OASDI (Baseline)"] = data["Net Interest"] / data["Revenues ex SS OASDI"]
 
+    # add a baseline SS OASDI revenues column
+    data["SS OASDI Revenues"] = data["Total Revenues"] - data["Revenues ex SS OASDI"]
+
     # add a projected average rate on federal debt column
     data["Average Rate on Federal Debt (Projected)"] = np.where(
-        data["Year"].astype(int) < 2026, 
+        data["Year"].astype(int) < 2025, 
         data["Average Rate on Federal Debt"], 
-        data["Average Rate on Federal Debt"] + (interest_rate_yearly_increase * (data["Year"].astype(int) - 2025)))
+        data["Average Rate on Federal Debt"] + (interest_rate_yearly_increase * (data["Year"].astype(int) - 2024)))
     
     # add a projected revenues column
     data["Total Revenues (Projected)"] = np.where(
-        data["Year"].astype(int) < 2026, 
+        data["Year"].astype(int) < 2025, 
         data["Total Revenues"], 
-        data["Total Revenues"] + (revenues_yearly_increase * (data["Year"].astype(int) - 2025)))
+        # data["Total Revenues"] + (revenues_yearly_increase * (data["Year"].astype(int) - 2025)))
+        data["Total Revenues"] + (1 + (cagr_revenues / 100) ** (data["Year"].astype(int) - 2024)))
     
     # add a projected revenues ex SS OASDI column
     data["Revenues ex SS OASDI (Projected)"] = np.where(
-        data["Year"].astype(int) < 2026, 
+        data["Year"].astype(int) < 2025, 
         data["Revenues ex SS OASDI"], 
-        data["Revenues ex SS OASDI"] + (revenues_yearly_increase * (data["Year"].astype(int) - 2025)))
+        data["SS OASDI Revenues"] + data["Total Revenues (Projected)"])
       
     # add a projected interest / revenues column
     data["Net Interest / Revenues (Projected)"] = np.where(
-        data["Year"].astype(int) < 2026, 
+        data["Year"].astype(int) < 2025, 
         data["Net Interest / Revenues (Baseline)"], 
         data["Average Rate on Federal Debt (Projected)"] * data["Debt Balance"] / data["Total Revenues (Projected)"])
     
     # add a projected interest / revenues ex SS OASDI column
     data["Net Interest / Revenues ex SS OASDI (Projected)"] = np.where(
-        data["Year"].astype(int) < 2026, 
+        data["Year"].astype(int) < 2025, 
         data["Net Interest / Revenues ex SS OASDI (Baseline)"], 
         data["Average Rate on Federal Debt (Projected)"] * data["Debt Balance"] / data["Revenues ex SS OASDI (Projected)"])
 
@@ -144,12 +149,15 @@ def plot_interest_coverage(interest_rate, revenues):
 interest_rate_lowerbound = 0
 interest_rate_upperbound = 15
 
-revenues_lower_bound = 10000
-revenues_upper_bound = 20000
+# revenues_lower_bound = 10000
+# revenues_upper_bound = 20000
+
+cagr_revenues_lower_bound = -3
+cagr_revenues_upper_bound = 8
 
 with gr.Blocks() as interface:
     # Create the image output
-    graph = gr.Image(type="filepath", label = "Graph", value = plot_interest_coverage(baseline_interest_rate, baseline_revenues))
+    graph = gr.Image(type="filepath", label = "Graph", value = plot_interest_coverage(baseline_interest_rate, baseline_cagr_revenues))
     
     # Create the slider input below the image for projected interest rate
     interest_rate_slider = gr.Slider(
@@ -161,27 +169,31 @@ with gr.Blocks() as interface:
     )
 
     # Create the slider input below the image for projected revenues
-    revenues_slider = gr.Slider(
-        revenues_lower_bound, 
-        revenues_upper_bound, 
-        step = 50,
-        value = baseline_revenues, 
-        label = "2054 Projected Revenues ($B)"
+    cagr_revenues_slider = gr.Slider(
+        cagr_revenues_lower_bound, 
+        cagr_revenues_upper_bound, 
+        step = 0.01,
+        value = baseline_cagr_revenues, 
+        label = "Revenues Compound Annual Growth Rate through 2054"
     )
 
-    gr.Markdown('<p style="font-size:11px;">Source: CBO June 2024  An Update to the Budget and Economic Outlook: 2024 to 2034, March 2024 report The Long-Term Budget Outlook: 2024 to 2054, and author\'s calculations. Scenario of higher interest rate is author\'s calculations. Data points for 2035-2054 calculated to build on CBO\'s June 2024 10-year update and be consistent with the March 2024 long-term report. Historical Social Security OASDI payroll tax revenue from Table 4-3 of the SSA\'s Trust Fund Data, and projections from the CBO\'s August 2024 Long Term Projections for Social Security.</p>')
+    gr.Markdown('<p style="font-size:11px;">Source: CBO June 2024  An Update to the Budget and Economic Outlook: 2024 to 2034, '
+    'March 2024 report The Long-Term Budget Outlook: 2024 to 2054, and author\'s calculations. Scenario of higher interest rate and revenues'
+    'is author\'s calculations. Data points for 2035-2054 calculated to build on CBO\'s June 2024 10-year update and be consistent '
+    'with the March 2024 long-term report. Historical Social Security OASDI payroll tax revenue from Table 4-3 of the SSA\'s '
+    'Trust Fund Data, and projections from the CBO\'s August 2024 Long Term Projections for Social Security.</p>')
 
     # Set up an action that updates the graph when the interest rate slider value changes
     interest_rate_slider.change(
         plot_interest_coverage, 
-        inputs = [interest_rate_slider, revenues_slider], 
+        inputs = [interest_rate_slider, cagr_revenues_slider], 
         outputs = graph
     )
 
     # Set up an action that updates the graph when the revenues slider value changes
-    revenues_slider.change(
+    cagr_revenues_slider.change(
         plot_interest_coverage, 
-        inputs = [interest_rate_slider, revenues_slider], 
+        inputs = [interest_rate_slider, cagr_revenues_slider], 
         outputs = graph
     )