diff --git a/conda.recipe/meta.yaml b/conda.recipe/meta.yaml
index c91f99362..00ec460ee 100755
--- a/conda.recipe/meta.yaml
+++ b/conda.recipe/meta.yaml
@@ -9,19 +9,21 @@ requirements:
   build:
     - python
     - "taxcalc>=2.4.2"
+    - "paramtools>=0.7.1"
     - setuptools
-    - scipy
+    - "scipy>=0.18.1"
     - matplotlib
-    - dask
+    - "dask>=0.20.0"
     - mkl
 
   run:
     - python
     - "taxcalc>=2.4.2"
+    - "paramtools>=0.7.1"
     - setuptools
-    - scipy
+    - "scipy>=0.18.1"
     - matplotlib
-    - dask
+    - "dask>=0.20.0"
     - mkl
 
 about:
@@ -47,7 +49,6 @@ test:
     - ogusa.parameter_plots
     - ogusa.parameter_tables
     - ogusa.parameters
-    - ogusa.parametersbase
     - ogusa.postprocess
     - ogusa.tax
     - ogusa.txfunc
diff --git a/docs/source/parametersbase.rst b/docs/source/parametersbase.rst
deleted file mode 100644
index 7e89c5615..000000000
--- a/docs/source/parametersbase.rst
+++ /dev/null
@@ -1,18 +0,0 @@
-.. _parametersbasae:
-
-OG-USA Parameters Base Class
-=================================================
-
-**OG-USA Parameters**
-
-ogusa.parametersbase
-------------------------------------------
-
-.. currentmodule:: ogusa.parametersbase
-
-.. automodule:: ogusa.parametersbase
-  :members:
-
-.. autoclass:: ParametersBase
-  :members: default_data, _params_dict_from_json_file, _update, _expand_array,
-    simple_eval
diff --git a/docs/source/public_api.rst b/docs/source/public_api.rst
index 18acd8b88..6e09bf2e4 100644
--- a/docs/source/public_api.rst
+++ b/docs/source/public_api.rst
@@ -30,7 +30,6 @@ There is also a link to the source code for each documented member.
    parameter_plots
    parameter_tables
    parameters
-   parametersbase
    postprocess
    tax
    txfunc
diff --git a/environment.yml b/environment.yml
index 0ce11df42..524487da0 100644
--- a/environment.yml
+++ b/environment.yml
@@ -6,10 +6,11 @@ dependencies:
 - python
 - setuptools
 - mkl
-- scipy>=0.18.1
+- "scipy>=0.18.1"
 - matplotlib
-- taxcalc>=2.4.2
-- dask>=0.20.0
+- "taxcalc>=2.4.2"
+- "dask>=0.20.0"
+- "paramtools>=0.7.1"
 - pytest
 - pytest-pep8
 - pytest-xdist
diff --git a/ogusa/__init__.py b/ogusa/__init__.py
index abbd7d076..c6e61a166 100644
--- a/ogusa/__init__.py
+++ b/ogusa/__init__.py
@@ -18,7 +18,6 @@
 from ogusa.parameter_plots import *
 from ogusa.parameter_tables import *
 from ogusa.parameters import *
-from ogusa.parametersbase import *
 from ogusa.postprocess import *
 from ogusa.tax import *
 from ogusa.txfunc import *
diff --git a/ogusa/default_parameters.json b/ogusa/default_parameters.json
index c93d13a98..5895973c9 100644
--- a/ogusa/default_parameters.json
+++ b/ogusa/default_parameters.json
@@ -1,1248 +1,2694 @@
 {
+    "schema": {
+        "labels": {}
+    },
     "frisch": {
-        "long_name": "Frisch elasticity of labor supply",
+        "title": "Frisch elasticity of labor supply",
         "description": "Frisch elasticity of labor supply",
         "notes": "See Altonji (JPE, 1996) and Peterman (Econ Inquiry, 2016) for estimates of the Frisch elasticity",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.4,
-        "range": {"min": 0.2, "max": 0.62},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.4
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.2,
+                "max": 0.62
+            }
+        }
     },
     "g_y_annual": {
-        "long_name": "Exogenous growth rate of labor augmenting technological change",
+        "title": "Exogenous growth rate of labor augmenting technological change",
         "description": "Growth rate of labor augmenting technological change",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.03,
-        "range": {"min": -0.01, "max": 0.04},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.03
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": -0.01,
+                "max": 0.04
+            }
+        }
     },
     "S": {
-        "long_name": "Maximum number of periods of economic life of model agent",
+        "title": "Maximum number of periods of economic life of model agent",
         "description": "Maximum number of periods of economic life of model agent",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 80,
-        "range": {"min": 3, "max": 80},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 80
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 3,
+                "max": 80
+            }
+        }
     },
     "J": {
-        "long_name": "Number of different labor productivity types of agents",
+        "title": "Number of different labor productivity types of agents",
         "description": "Number of different labor productivity types of agents",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 7,
-        "range": {"min": 1, "max": 100},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 7
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 1,
+                "max": 100
+            }
+        }
     },
     "T": {
-        "long_name": "Number of periods until it is assumed that the model reaches its steady state",
+        "title": "Number of periods until it is assumed that the model reaches its steady state",
         "description": "Number of periods until it is assumed that the model reaches its steady state",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 320,
-        "range": {"min": "S", "max": 1000},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 320
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 3,
+                "max": 1000
+            }
+        }
     },
     "lambdas": {
-        "long_name": "Fraction of population of each labor productivity type",
+        "title": "Fraction of population of each labor productivity type",
         "description": "Fraction of population of each labor productivity type",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.25, 0.25, 0.2, 0.1, 0.1, 0.09, 0.01],
-        "range": {"min": 0.0, "max": 1.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.25,
+                    0.25,
+                    0.2,
+                    0.1,
+                    0.1,
+                    0.09,
+                    0.01
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "starting_age": {
-        "long_name": "Age at which households become economically active",
+        "title": "Age at which households become economically active",
         "description": "Age at which households become economically active",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 20,
-        "range": {"min": 0, "max": "ending_age - 1"},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 20
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0,
+                "max": 80
+            }
+        }
     },
     "ending_age": {
-        "long_name": "Maximum age a household can live until",
+        "title": "Maximum age a household can live until",
         "description": "Maximum age a household can live until",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 100,
-        "range": {"min": "starting_age + 1", "max": 120},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 100
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0,
+                "max": 120
+            }
+        }
     },
     "constant_demographics": {
-        "long_name": "Use constant demographics.",
+        "title": "Use constant demographics.",
         "description": "Use constant demographics.",
         "notes": "This boolean allows one to use empirical mortality rates, but keep the population distribution constant across periods.  Note that immigration is shut off when this is true.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "beta_annual": {
-        "long_name": "Annual rate of time preference for households",
+        "title": "Annual rate of time preference for households",
         "description": "Annual rate of time preference for households",
         "notes": "Default value from Carroll (JME, 2009)",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.96,
-        "range": {"min": 0.0, "max": 0.9999},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.96
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.9999
+            }
+        }
     },
     "sigma": {
-        "long_name": "Coefficient of relative risk aversion in household utility function",
+        "title": "Coefficient of relative risk aversion in household utility function",
         "description": "Coefficient of relative risk aversion in household utility function",
         "notes": "Default value from Attanasio, Banks, Meghir and Weber (JEBS, 1999)",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1.5,
-        "range": {"min": 1.0, "max": 3.5},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1.5
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 1.0,
+                "max": 3.5
+            }
+        }
     },
     "gamma_s": {
-      "long_name": "Bond's share of assets in the household portfolio problem",
-      "description": "Bond's share of assets in the household portfolio problem",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.5,
-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
+        "title": "Bond's share of assets in the household portfolio problem",
+        "description": "Bond's share of assets in the household portfolio problem",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.5
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "epsilon_s": {
-        "long_name": "Elasticity of substitution between bonds and equity in the household portfolio problem",
+        "title": "Elasticity of substitution between bonds and equity in the household portfolio problem",
         "description": "Elasticity of substitution between bonds and equity in the household portfolio problem",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1.0,
-        "range": {"min": 0.1, "max": 10.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.1,
+                "max": 10.0
+            }
+        }
     },
     "gamma": {
-      "long_name": "Capital's share of output in firm production funtion",
-      "description": "Capital's share of output in firm production funtion",
-      "notes": "Histroical value in U.S. is about 0.33, but Elsby, Hobijn, and Sahin (BPEA, 2013) find capital's share is increasing, so default value is above this",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.35,
-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
+        "title": "Capital's share of output in firm production funtion",
+        "description": "Capital's share of output in firm production funtion",
+        "notes": "Histroical value in U.S. is about 0.33, but Elsby, Hobijn, and Sahin (BPEA, 2013) find capital's share is increasing, so default value is above this",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.35
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "epsilon": {
-        "long_name": "Elasticity of substitution between capital and labor in firm production function",
+        "title": "Elasticity of substitution between capital and labor in firm production function",
         "description": "Elasticity of substitution between capital and labor in firm production function",
         "notes": "If epislon=1, then production function is Cobb-Douglas.  If epislon=0, then production function is perfect substitutes.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1.0,
-        "range": {"min": 0.2, "max": 10.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.2,
+                "max": 10.0
+            }
+        }
     },
     "Z": {
-        "long_name": "Total factor productivity in firm production function",
+        "title": "Total factor productivity in firm production function",
         "description": "Total factor productivity in firm production function",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [1.0],
-        "range": {"min": 0.0, "max": 5.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    1.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 5.0
+            }
+        }
     },
     "delta_annual": {
-        "long_name": "Annual rate of economic depreciation of capital",
+        "title": "Annual rate of economic depreciation of capital",
         "description": "Annual rate of economic depreciation of capital",
         "notes": "Approximately the value from Kehoe calibration exercise: http://www.econ.umn.edu/~tkehoe/classes/calibration-04.pdf",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.05,
-        "range": {"min": 0.0, "max": 1.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.05
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "ltilde": {
-        "long_name": "Total time endowment of household",
+        "title": "Total time endowment of household",
         "description": "Total time endowment of household",
         "notes": "Can be normalized to 1.0 without loss of generality",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1.0,
-        "range": {"min": 0.01, "max": 5.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.01,
+                "max": 5.0
+            }
+        }
     },
     "small_open": {
-        "long_name": "Boolean to indicate using a small open economy model",
+        "title": "Boolean to indicate using a small open economy model",
         "description": "Boolean to indicate using a small open economy model",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "world_int_rate": {
-        "long_name": "Exogenous annual world interest rate to be used when modeling a small open economy",
+        "title": "Exogenous annual world interest rate to be used when modeling a small open economy",
         "description": "Exogenous annual world interest rate to be used when modeling a small open economy",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.04],
-        "range": {"min": 0.01, "max": 0.08},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
-    },
-    "initial_foreign_debt_ratio":{
-      "long_name": "Share of government debt held by foreigners in model start year",
-      "description": "Share of government debt held by foreigners in model start year",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.0,
-      "range": {"min": 0.00, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.04
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.01,
+                "max": 0.08
+            }
+        }
+    },
+    "initial_foreign_debt_ratio": {
+        "title": "Share of government debt held by foreigners in model start year",
+        "description": "Share of government debt held by foreigners in model start year",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "zeta_D": {
-        "long_name": "Share of new debt issues from government that are purchased by foreigners",
+        "title": "Share of new debt issues from government that are purchased by foreigners",
         "description": "Share of new debt issues from government that are purchased by foreigners",
         "notes": "This value is about 0.4 historically for the U.S., set to zero to have closed econ as default",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0],
-        "range": {"min": 0.00, "max": 1.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "zeta_K": {
-        "long_name": "Share of excess demand for capital that is supplied by foreingers",
+        "title": "Share of excess demand for capital that is supplied by foreingers",
         "description": "Share of excess demand for capital that is supplied by foreingers",
         "notes": "Set to 0.1 when running large-open verion of US economy, but hard to find data to pin this down",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0],
-        "range": {"min": 0.00, "max": 1.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "tG1": {
-        "long_name": "Number of model periods until budget closure rule kicks in",
+        "title": "Number of model periods until budget closure rule kicks in",
         "description": "Number of model periods until budget closure rule kicks in",
         "notes": "It may make sense for this tG1 to exceed the length of the budget window one is looking at.  But it must also not be too late into the time path that a steady-state won't be reached by time T.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 20,
-        "range": {"min": 0, "max": "T / 2"},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 20
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0,
+                "max": 300
+            }
+        }
     },
     "tG2": {
-        "long_name": "Number of model periods until budget closure ends and budgetary variables jump to steady-state values",
+        "title": "Number of model periods until budget closure ends and budgetary variables jump to steady-state values",
         "description": "Number of model periods until budget closure ends and budgetary variables jump to steady-state values",
         "notes": "The number of periods until the closure rule ends must not exceed T, the time at which the model is assumed to reach the steady-state.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 256,
-        "range": {"min": 0, "max": "T"},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 256
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0,
+                "max": 500
+            }
+        }
     },
     "alpha_T": {
-        "long_name": "Exogenous ratio of government transfers to GDP when budget balance is false.",
+        "title": "Exogenous ratio of government transfers to GDP when budget balance is false.",
         "description": "Exogenous ratio of government transfers to GDP when budget balance is false.",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.09],
-        "range": {"min": 0.0, "max": 0.3},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.09
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.3
+            }
+        }
     },
     "alpha_G": {
-        "long_name": "Exogenous ratio of government spending to GDP when budget balance is false.",
+        "title": "Exogenous ratio of government spending to GDP when budget balance is false.",
         "description": "Exogenous ratio of government spending to GDP when budget balance is false.",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.05],
-        "range": {"min": 0.0, "max": 0.3},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.05
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.3
+            }
+        }
     },
     "rho_G": {
-        "long_name": "Speed of convergence to a stable government budget deficit for periods [tG1, tG2-1]",
+        "title": "Speed of convergence to a stable government budget deficit for periods [tG1, tG2-1]",
         "description": "Speed of convergence to a stable government budget deficit for periods [tG1, tG2-1]",
         "notes": "Lower rho_G => slower convergence.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.1,
-        "range": {"min": 0.01, "max": 0.9},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.1
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.01,
+                "max": 0.9
+            }
+        }
     },
     "debt_ratio_ss": {
-        "long_name": "Debt to GDP ratio to be achieved in the steady state",
+        "title": "Debt to GDP ratio to be achieved in the steady state",
         "description": "Debt to GDP ratio to be achieved in the steady state",
         "notes": "Note that depending upon the tax policy parameters, some debt to GDP ratios may not be achievable with positive government spending",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1.0,
-        "range": {"min": 0.0, "max": 5.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 5.0
+            }
+        }
     },
     "initial_debt_ratio": {
-        "long_name": "Debt to GDP ratio in the initial period",
+        "title": "Debt to GDP ratio in the initial period",
         "description": "Debt to GDP ratio in the initial period",
         "notes": "Should be calibrated based on government debt held by the public to GDP in the model start year.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.78,
-        "range": {"min": 0.0, "max": 2.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.78
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 2.0
+            }
+        }
     },
     "r_gov_scale": {
-        "long_name": "Scale parameter to determine government interest rate.",
+        "title": "Scale parameter to determine government interest rate.",
         "description": "Parameter to scale the market interest rate to find interest rate on government debt.",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1.0,
-        "range": {"min": 0.0, "max": 2.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 2.0
+            }
+        }
     },
     "r_gov_shift": {
-        "long_name": "Shift parameter to determine government interest rate.",
+        "title": "Shift parameter to determine government interest rate.",
         "description": "Parameter to shift the market interest rate to find interest rate on government debt.",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.0,
-        "range": {"min": 0.0, "max": 0.2},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.2
+            }
+        }
     },
     "tau_b": {
-        "long_name": "Entity level tax on businesses",
+        "title": "Entity level tax on businesses",
         "description": "Entity level tax on businesses",
         "notes": "With a single representative firm, this should be a weighted average of the entity level rate on pass-through businesses (0) and the corporate income tax rate.  It does not reflect statutory rates, but rather effective rates.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0357],
-        "range": {"min": 0.00, "max": 0.9},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.0357
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.9
+            }
+        }
     },
     "tau_c": {
-        "long_name": "Consumption tax rate",
+        "title": "Consumption tax rate",
         "description": "Consumption tax rate",
         "notes": "This policy parameter represents the effective consumption tax rate from sales taxes, VATs, and excise taxes.  To capture exemptions of certain goods, this is assumed to vary by age and ability type.  It is thus a SxJ matrix.",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0],
-        "range": {"min": 0.00, "max": 0.9},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": [
+                    0.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.9
+            }
+        }
     },
     "delta_tau_annual": {
-        "long_name": "Annual rate of depreciation of capital for tax purposes",
+        "title": "Annual rate of depreciation of capital for tax purposes",
         "description": "Annual rate of depreciation of capital for tax purposes",
-        "notes": "B-Tax can help to calibrate this parameter",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.027],
-        "range": {"min": 0.0, "max": 1.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "notes": "Cost-of-Capital-Calculator can help to calibrate this parameter",
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.027
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
     },
     "h_wealth": {
-        "long_name": "Numerator in wealth tax function",
+        "title": "Numerator in wealth tax function",
         "description": "Numerator in wealth tax function",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.1],
-        "range": {"min": 0.0, "max": 10.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.1
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 10.0
+            }
+        }
     },
     "m_wealth": {
-        "long_name": "Term in denominator in wealth tax function",
+        "title": "Term in denominator in wealth tax function",
         "description": "Term in denominator in wealth tax function",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [1.0],
-        "range": {"min": 0.0, "max": 10.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    1.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 10.0
+            }
+        }
     },
     "p_wealth": {
-        "long_name": "Scale parameter in wealth tax function",
+        "title": "Scale parameter in wealth tax function",
         "description": "Scale parameter in wealth tax function",
         "notes": "Set to 0 to have no wealth tax",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0],
-        "range": {"min": 0.0, "max": 10.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 10.0
+            }
+        }
     },
     "tau_bq": {
-        "long_name": "Linear tax rate on bequests",
+        "title": "Linear tax rate on bequests",
         "description": "Linear tax rate on bequests",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0],
-        "range": {"min": 0.0, "max": 0.99},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.99
+            }
+        }
     },
     "tau_payroll": {
-        "long_name": "Linear payroll tax rate",
+        "title": "Linear payroll tax rate",
         "description": "Linear payroll tax rate",
         "notes": "Set to zero as default since tax functions include income and payroll taxes",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [0.0],
-        "range": {"min": 0.0, "max": 0.99},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    0.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 0.99
+            }
+        }
     },
     "chi_b": {
-        "long_name": "Utility weight on bequests",
+        "title": "Utility weight on bequests",
         "description": "Household utility weight on bequests",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": [80.0, 80.0, 80.0, 80.0, 80.0, 80.0, 80.0],
-        "range": {"min": 0.0, "max": 10000.0},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    80.0,
+                    80.0,
+                    80.0,
+                    80.0,
+                    80.0,
+                    80.0,
+                    80.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 10000.0
+            }
+        }
     },
     "eta": {
-      "long_name": "Government transfer allocation",
-      "description": "Matrix that allocated government transfers across households.",
-      "notes": "This SxJ matrix gives the fraction of total aggregate transfers going to each age s and ability type j.",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": [[3.95156539e-03, 3.95156539e-03, 3.16125231e-03, 1.58062616e-03,
-               1.58062616e-03, 1.42256354e-03, 1.58062616e-04],
-              [3.97057633e-03, 3.97057633e-03, 3.17646106e-03, 1.58823053e-03,
-               1.58823053e-03, 1.42940748e-03, 1.58823053e-04],
-              [3.99140521e-03, 3.99140521e-03, 3.19312416e-03, 1.59656208e-03,
-               1.59656208e-03, 1.43690587e-03, 1.59656208e-04],
-              [4.01335125e-03, 4.01335125e-03, 3.21068100e-03, 1.60534050e-03,
-               1.60534050e-03, 1.44480645e-03, 1.60534050e-04],
-              [4.03533960e-03, 4.03533960e-03, 3.22827168e-03, 1.61413584e-03,
-               1.61413584e-03, 1.45272226e-03, 1.61413584e-04],
-              [4.05670193e-03, 4.05670193e-03, 3.24536154e-03, 1.62268077e-03,
-               1.62268077e-03, 1.46041269e-03, 1.62268077e-04],
-              [4.07611530e-03, 4.07611530e-03, 3.26089224e-03, 1.63044612e-03,
-               1.63044612e-03, 1.46740151e-03, 1.63044612e-04],
-              [4.09333545e-03, 4.09333545e-03, 3.27466836e-03, 1.63733418e-03,
-               1.63733418e-03, 1.47360076e-03, 1.63733418e-04],
-              [4.10837135e-03, 4.10837135e-03, 3.28669708e-03, 1.64334854e-03,
-               1.64334854e-03, 1.47901369e-03, 1.64334854e-04],
-              [4.12086399e-03, 4.12086399e-03, 3.29669119e-03, 1.64834560e-03,
-               1.64834560e-03, 1.48351104e-03, 1.64834560e-04],
-              [4.13081400e-03, 4.13081400e-03, 3.30465120e-03, 1.65232560e-03,
-               1.65232560e-03, 1.48709304e-03, 1.65232560e-04],
-              [4.13889370e-03, 4.13889370e-03, 3.31111496e-03, 1.65555748e-03,
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-              [6.99517695e-04, 6.99517695e-04, 5.59614156e-04, 2.79807078e-04,
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-              [5.78728940e-04, 5.78728940e-04, 4.62983152e-04, 2.31491576e-04,
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-              [4.69422939e-04, 4.69422939e-04, 3.75538351e-04, 1.87769176e-04,
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-              [3.73067125e-04, 3.73067125e-04, 2.98453700e-04, 1.49226850e-04,
-               1.49226850e-04, 1.34304165e-04, 1.49226850e-05],
-              [2.90043322e-04, 2.90043322e-04, 2.32034658e-04, 1.16017329e-04,
-               1.16017329e-04, 1.04415596e-04, 1.16017329e-05],
-              [2.20585214e-04, 2.20585214e-04, 1.76468171e-04, 8.82340856e-05,
-               8.82340856e-05, 7.94106770e-05, 8.82340856e-06],
-              [1.63827444e-04, 1.63827444e-04, 1.31061955e-04, 6.55309777e-05,
-               6.55309777e-05, 5.89778799e-05, 6.55309777e-06],
-              [1.18543187e-04, 1.18543187e-04, 9.48345498e-05, 4.74172749e-05,
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-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
+        "title": "Government transfer allocation",
+        "description": "Matrix that allocated government transfers across households.",
+        "notes": "This SxJ matrix gives the fraction of total aggregate transfers going to each age s and ability type j.",
+        "type": "float",
+        "number_dims": 2,
+        "value": [
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     },
     "zeta": {
-      "long_name": "Bequest distribution process",
-      "description": "Matrix that describes the bequest distribution process.",
-      "notes": "This SxJ matrix gives the fraction of total aggregate bequests going to each age s and ability type j.",
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-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
+        "title": "Bequest distribution process",
+        "description": "Matrix that describes the bequest distribution process.",
+        "notes": "This SxJ matrix gives the fraction of total aggregate bequests going to each age s and ability type j.",
+        "type": "float",
+        "number_dims": 2,
+        "value": [
+            {
+                "value": [
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+                    40.86564363,
+                    41.73645892,
+                    42.6208256,
+                    43.37786072,
+                    45.38166073,
+                    46.22395387,
+                    50.21419653,
+                    51.05246704,
+                    53.86896121,
+                    53.90029708,
+                    61.83586775,
+                    64.87563699,
+                    66.91207845,
+                    68.07449767,
+                    71.27919965,
+                    73.57195873,
+                    74.95045988,
+                    76.6230815
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 10000.0
+            }
+        }
     },
     "constant_rates": {
-        "long_name": "Flag to use linear tax functions",
+        "title": "Flag to use linear tax functions",
         "description": "Flag to use linear tax functions",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "zero_taxes": {
-        "long_name": "Flag to run model without any individual income taxes.",
+        "title": "Flag to run model without any individual income taxes.",
         "description": "Flag to run model without any individual income taxes.",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "analytical_mtrs": {
-        "long_name": "Flag to use analytically derived marginal tax rates in tax functions",
+        "title": "Flag to use analytically derived marginal tax rates in tax functions",
         "description": "Flag to use analytically derived marginal tax rates in tax functions",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "age_specific": {
-        "long_name": "Flag to use analytically derived marginal tax rates in tax functions",
+        "title": "Flag to use analytically derived marginal tax rates in tax functions",
         "description": "Flag to use analytically derived marginal tax rates in tax functions",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": true,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
-    },
-    "retirement_age":{
-      "long_name": "Age at which agents can collect social security benefits.",
-      "description": "Age at which agents can collect social security benefits.",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": true,
-      "string_value": false,
-      "value": [65],
-      "range": {"min": "starting_age", "max": "ending_age"},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "AIME_num_years":{
-      "long_name": "Number of years used to compute average index monthly earnings (AIME).",
-      "description": "Number of years used to compute average index monthly earnings (AIME).",
-      "notes": "AIME is computed using average earnings from the highest earnings years for the number of years specified here.",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": true,
-      "string_value": false,
-      "value": 35,
-      "range": {"min": 1, "max": "S"},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "AIME_bkt_1":{
-      "long_name": "Upper bound to the first average index monthly earnings (AIME) bracket.",
-      "description": "Upper bound to the first average index monthly earnings (AIME) bracket.",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 749.0,
-      "range": {"min": 0.0, "max": "AIME_bkt_2"},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "AIME_bkt_2":{
-      "long_name": "Upper bound to the second average index monthly earnings (AIME) bracket.",
-      "description": "Upper bound to the second average index monthly earnings (AIME) bracket.",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 4517.0,
-      "range": {"min": "AIME_bkt_1", "max": 9999999999999.9},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "PIA_rate_bkt_1":{
-      "long_name": "The rate used to determine the primary insurance amount (PIA) in the first bracket for average index monthly earnings (AIME).",
-      "description": "The rate used to determine the primary insurance amount (PIA) in the first bracket for average index monthly earnings (AIME).",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.9,
-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "PIA_rate_bkt_2":{
-      "long_name": "The rate used to determine the primary insurance amount (PIA) in the second bracket for average index monthly earnings (AIME).",
-      "description": "The rate used to determine the primary insurance amount (PIA) in the second bracket for average index monthly earnings (AIME).",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.32,
-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "PIA_rate_bkt_3":{
-      "long_name": "The rate used to determine the primary insurance amount (PIA) in the third bracket for average index monthly earnings (AIME).",
-      "description": "The rate used to determine the primary insurance amount (PIA) in the third bracket for average index monthly earnings (AIME).",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.15,
-      "range": {"min": 0.0, "max": 1.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "PIA_maxpayment":{
-      "long_name": "The maximum primary insurance amount (PIA) payment.",
-      "description": "The maximum primary insurance amount (PIA) payment.",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 3501.0,
-      "range": {"min": 0.0, "max": 9999999999999.9},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "PIA_minpayment":{
-      "long_name": "The minimum primary insurance amount (PIA) payment.",
-      "description": "The minimum primary insurance amount (PIA) payment.",
-      "notes": "",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": 0.0,
-      "range": {"min": 0.0, "max": "PIA_maxpayment"},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
-    },
-    "replacement_rate_adjust":{
-      "long_name": "Adjustment to the social security retirement benefits replacement rate.",
-      "description": "Adjustment to the social security retirement benefits replacement rate.",
-      "notes": "This parameter willy only vary along the time path.  It is assumed to be one in the steady state.  The steady state retirement rate can be adjusted by changing the parameters of the retirement benefits function.",
-      "col_var": "",
-      "col_label": "",
-      "boolean_value": false,
-      "integer_value": false,
-      "string_value": false,
-      "value": [1.0],
-      "range": {"min": 0.0, "max": 10.0},
-      "out_of_range_minmsg": "",
-      "out_of_range_maxmsg": "",
-      "out_of_range_action": "stop",
-      "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": true
+            }
+        ],
+        "validators": {}
+    },
+    "retirement_age": {
+        "title": "Age at which agents can collect social security benefits.",
+        "description": "Age at which agents can collect social security benefits.",
+        "notes": "",
+        "type": "int",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    65
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0,
+                "max": 100
+            }
+        }
+    },
+    "AIME_num_years": {
+        "title": "Number of years used to compute average index monthly earnings (AIME).",
+        "description": "Number of years used to compute average index monthly earnings (AIME).",
+        "notes": "AIME is computed using average earnings from the highest earnings years for the number of years specified here.",
+        "type": "int",
+        "value": [
+            {
+                "value": 35
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 1,
+                "max": 80
+            }
+        }
+    },
+    "AIME_bkt_1": {
+        "title": "Upper bound to the first average index monthly earnings (AIME) bracket.",
+        "description": "Upper bound to the first average index monthly earnings (AIME) bracket.",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 749.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 9999999999.0
+            }
+        }
+    },
+    "AIME_bkt_2": {
+        "title": "Upper bound to the second average index monthly earnings (AIME) bracket.",
+        "description": "Upper bound to the second average index monthly earnings (AIME) bracket.",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 4517.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 9999999999999.9
+            }
+        }
+    },
+    "PIA_rate_bkt_1": {
+        "title": "The rate used to determine the primary insurance amount (PIA) in the first bracket for average index monthly earnings (AIME).",
+        "description": "The rate used to determine the primary insurance amount (PIA) in the first bracket for average index monthly earnings (AIME).",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.9
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
+    },
+    "PIA_rate_bkt_2": {
+        "title": "The rate used to determine the primary insurance amount (PIA) in the second bracket for average index monthly earnings (AIME).",
+        "description": "The rate used to determine the primary insurance amount (PIA) in the second bracket for average index monthly earnings (AIME).",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.32
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
+    },
+    "PIA_rate_bkt_3": {
+        "title": "The rate used to determine the primary insurance amount (PIA) in the third bracket for average index monthly earnings (AIME).",
+        "description": "The rate used to determine the primary insurance amount (PIA) in the third bracket for average index monthly earnings (AIME).",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.15
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 1.0
+            }
+        }
+    },
+    "PIA_maxpayment": {
+        "title": "The maximum primary insurance amount (PIA) payment.",
+        "description": "The maximum primary insurance amount (PIA) payment.",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 3501.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 9999999999999.9
+            }
+        }
+    },
+    "PIA_minpayment": {
+        "title": "The minimum primary insurance amount (PIA) payment.",
+        "description": "The minimum primary insurance amount (PIA) payment.",
+        "notes": "",
+        "type": "float",
+        "value": [
+            {
+                "value": 0.0
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 999999999.9
+            }
+        }
+    },
+    "replacement_rate_adjust": {
+        "title": "Adjustment to the social security retirement benefits replacement rate.",
+        "description": "Adjustment to the social security retirement benefits replacement rate.",
+        "notes": "This parameter willy only vary along the time path.  It is assumed to be one in the steady state.  The steady state retirement rate can be adjusted by changing the parameters of the retirement benefits function.",
+        "type": "float",
+        "number_dims": 1,
+        "value": [
+            {
+                "value": [
+                    1.0
+                ]
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.0,
+                "max": 10.0
+            }
+        }
     },
     "budget_balance": {
-        "long_name": "Flag to balance government budget in each period",
+        "title": "Flag to balance government budget in each period",
         "description": "Flag to balance government budget in each period",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "baseline_spending": {
-        "long_name": "Flag to keep level of government spending and transfers constant between baseline and reform runs",
+        "title": "Flag to keep level of government spending and transfers constant between baseline and reform runs",
         "description": "Flag to keep level of government spending and transfers constant between baseline and reform runs",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": true,
-        "integer_value": false,
-        "string_value": false,
-        "value": false,
-        "range": {"min": false, "max": true},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "bool",
+        "value": [
+            {
+                "value": false
+            }
+        ],
+        "validators": {}
     },
     "start_year": {
-        "long_name": "Calendar year in which to start model analysis",
+        "title": "Calendar year in which to start model analysis",
         "description": "Calendar year in which to start model analysis",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 2019,
-        "range": {"min": 2013, "max": 2028},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 2019
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 2013,
+                "max": 2028
+            }
+        }
     },
     "tax_func_type": {
-        "long_name": "Functional form for individual income tax functions",
+        "title": "Functional form for individual income tax functions",
         "description": "Functional form for individual income tax functions",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": true,
-        "value": "DEP",
-        "range": {"possible_values": ["DEP", "DEP_totalinc", "GS", "linear"]},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "str",
+        "value": [
+            {
+                "value": "DEP"
+            }
+        ],
+        "validators": {
+            "choice": {
+                "choices": [
+                    "DEP",
+                    "DEP_totalinc",
+                    "GS",
+                    "linear"
+                ]
+            }
+        }
     },
     "nu": {
-        "long_name": "Parameter for convergence rate of functional iteration",
+        "title": "Parameter for convergence rate of functional iteration",
         "description": "Parameter for convergence rate of functional iteration",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 0.4,
-        "range": {"min": 0.01, "max": 0.5},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 0.4
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 0.01,
+                "max": 0.5
+            }
+        }
     },
     "maxiter": {
-        "long_name": "Max iterations for time path iteration",
+        "title": "Max iterations for time path iteration",
         "description": "Max iterations for time path iteration",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": true,
-        "string_value": false,
-        "value": 250,
-        "range": {"min": 2, "max": 500},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "int",
+        "value": [
+            {
+                "value": 250
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 2,
+                "max": 500
+            }
+        }
     },
     "mindist_SS": {
-        "long_name": "Tolerance for convergence of steady state solution",
+        "title": "Tolerance for convergence of steady state solution",
         "description": "Tolerance for convergence of steady state solution",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1e-9,
-        "range": {"min": 1e-13, "max": 0.001},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1e-09
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 1e-13,
+                "max": 0.001
+            }
+        }
     },
     "mindist_TPI": {
-        "long_name": "Tolerance for convergence of time path solution",
+        "title": "Tolerance for convergence of time path solution",
         "description": "Tolerance for convergence of time path solution",
         "notes": "",
-        "col_var": "",
-        "col_label": "",
-        "boolean_value": false,
-        "integer_value": false,
-        "string_value": false,
-        "value": 1e-5,
-        "range": {"min": 1e-13, "max": 0.001},
-        "out_of_range_minmsg": "",
-        "out_of_range_maxmsg": "",
-        "out_of_range_action": "stop",
-        "compatible_data": {"puf": true, "cps": true}
+        "type": "float",
+        "value": [
+            {
+                "value": 1e-05
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": 1e-13,
+                "max": 0.001
+            }
+        }
     }
 }
diff --git a/ogusa/execute.py b/ogusa/execute.py
index b4be24cac..1da53e0c2 100644
--- a/ogusa/execute.py
+++ b/ogusa/execute.py
@@ -3,6 +3,7 @@
 '''
 
 import pickle
+import cloudpickle
 import os
 import time
 from ogusa import SS, TPI, utils
@@ -66,6 +67,8 @@ def runner(output_base, baseline_dir, test=False, time_path=True,
     spec.update_specifications(og_spec)
     print('path for tax functions: ', spec.output_base)
     spec.get_tax_function_parameters(client, run_micro)
+    print('test versions? = = ', spec.test)
+    print('SS tolerance = ', spec.mindist_SS, ', S = ', spec.S)
 
     '''
     ------------------------------------------------------------------------
@@ -85,14 +88,16 @@ def runner(output_base, baseline_dir, test=False, time_path=True,
         pickle.dump(ss_outputs, open(ss_dir, "wb"))
         # Save pickle with parameter values for the run
         param_dir = os.path.join(baseline_dir, "model_params.pkl")
-        pickle.dump(spec, open(param_dir, "wb"))
+        with open(param_dir, "wb") as f:
+            cloudpickle.dump((spec), f)
     else:
         utils.mkdirs(os.path.join(output_base, "SS"))
         ss_dir = os.path.join(output_base, "SS/SS_vars.pkl")
         pickle.dump(ss_outputs, open(ss_dir, "wb"))
         # Save pickle with parameter values for the run
         param_dir = os.path.join(output_base, "model_params.pkl")
-        pickle.dump(spec, open(param_dir, "wb"))
+        with open(param_dir, "wb") as f:
+            cloudpickle.dump((spec), f)
 
     if time_path:
         '''
diff --git a/ogusa/parameters.py b/ogusa/parameters.py
index 20c65bf47..7a4a48917 100644
--- a/ogusa/parameters.py
+++ b/ogusa/parameters.py
@@ -5,33 +5,28 @@
 import numpy as np
 import scipy.interpolate as si
 import pkg_resources
+import paramtools
 
 # import ogusa
-from ogusa.parametersbase import ParametersBase
-from ogusa import elliptical_u_est
-from ogusa import demographics
-from ogusa import income
-from ogusa import txfunc
+from ogusa import elliptical_u_est, demographics, income, txfunc
 from ogusa.utils import (BASELINE_DIR, TC_LAST_YEAR, rate_conversion,
                          safe_read_pickle)
-# from ogusa import elliptical_u_est
+CURRENT_PATH = os.path.abspath(os.path.dirname(__file__))
 
 
-class Specifications(ParametersBase):
+class Specifications(paramtools.Parameters):
     '''
-    Inherits ParametersBase. Implements the PolicyBrain API for OG-USA
+    Inherits ParamTools Parameters abstract base class.
     '''
-    DEFAULTS_FILENAME = 'default_parameters.json'
+    defaults = os.path.join(CURRENT_PATH, "default_parameters.json")
+    array_first = True
 
     def __init__(self,
                  run_micro=False, output_base=BASELINE_DIR,
                  baseline_dir=BASELINE_DIR, test=False, time_path=True,
                  baseline=False, iit_reform={}, guid='', data='cps',
                  flag_graphs=False, client=None, num_workers=1):
-        super(Specifications, self).__init__()
-
-        # reads in default parameter values
-        self._vals = self._params_dict_from_json_file()
+        super().__init__()
 
         self.output_base = output_base
         self.baseline_dir = baseline_dir
@@ -70,13 +65,6 @@ def initialize(self):
             None
 
         '''
-        for name, data in self._vals.items():
-            intg_val = data.get('integer_value', None)
-            bool_val = data.get('boolean_value', None)
-            string_val = data.get('string_value', None)
-            values = data.get('value', None)
-            setattr(self, name, self._expand_array(values, intg_val,
-                                                   bool_val, string_val))
 
         if self.test:
             # Make smaller statespace for testing
@@ -207,6 +195,13 @@ def compute_default_params(self):
                          (self.S, 1, 1))), axis=0)
         setattr(self, 'eta',  eta_to_set)
 
+        # reshape lambdas
+        self.lambdas = self.lambdas.reshape(self.lambdas.shape[0], 1)
+        # cast integers as integers
+        self.S = int(self.S)
+        self.T = int(self.T)
+        self.J = int(self.J)
+
         # open economy parameters
         firm_r_annual = self.world_int_rate
         hh_r_annual = firm_r_annual
@@ -452,21 +447,6 @@ def read_tax_func_estimate(self, pickle_path, pickle_file):
 
         return dict_params
 
-    def default_parameters(self):
-        '''
-        Return Policy object same as self except with current-law policy.
-        Returns
-
-        Args:
-            None
-
-        Returns:
-            None
-
-        '''
-        dp = Specifications()
-        return dp
-
     def update_specifications(self, revision, raise_errors=True):
         '''
         Updates parameter specification with values in revision
@@ -502,234 +482,47 @@ def update_specifications(self, revision, raise_errors=True):
                 }
 
         '''
-        # check that all revisions dictionary keys are integers
-        if not isinstance(revision, dict):
-            raise ValueError('ERROR: revision is not a dictionary')
+        if not (isinstance(revision, dict) or isinstance(revision, str)):
+            raise ValueError(
+                'ERROR: revision is not a dictionary of string')
         if not revision:
             return  # no revision to implement
-        # check range of remaining revision_years
-        # validate revision parameter names and types
-        self.parameter_errors = ''
-        self.parameter_warnings = ''
-        self._validate_parameter_names_types(revision)
-        if not self._ignore_errors and self.parameter_errors:
-            raise ValueError(self.parameter_errors)
-        # implement the revision
-        revision_parameters = set()
-        revision_parameters.update(revision.keys())
-        self._update(revision)
-        # validate revision parameter values
-        self._validate_parameter_values(revision_parameters)
-        if self.parameter_errors and raise_errors:
-            raise ValueError('\n' + self.parameter_errors)
+        self.adjust(revision, raise_errors=raise_errors)
+        if self.errors and raise_errors:
+            raise ValueError('\n' + self.errors)
         self.compute_default_params()
 
     @staticmethod
-    def read_json_param_objects(revision):
-        '''
-        Read JSON file and convert to dictionary
-
-        Args:
-            revision (str): r JSON string with one or more
-                `PARAM: VALUE` pairs
-
-        Returns:
-            rev_dict (dict): formatted dictionary of parameters
-
+    def read_json_revision(obj):
         '''
-        # next process first reform parameter
-        if revision is None:
-            rev_dict = dict()
-        elif isinstance(revision, six.string_types):
-            if os.path.isfile(revision):
-                txt = open(revision, 'r').read()
-            else:
-                txt = revision
-            # strip out //-comments without changing line numbers
-            json_str = re.sub('//.*', ' ', txt)
-            # convert JSON text into a Python dictionary
-            try:
-                rev_dict = json.loads(json_str)
-            except ValueError as valerr:
-                msg = 'Policy reform text below contains invalid JSON:\n'
-                msg += str(valerr) + '\n'
-                msg += 'Above location of the first error may be approximate.\n'
-                msg += 'The invalid JSON reform text is between the lines:\n'
-                bline = 'XX----.----1----.----2----.----3----.----4'
-                bline += '----.----5----.----6----.----7'
-                msg += bline + '\n'
-                linenum = 0
-                for line in json_str.split('\n'):
-                    linenum += 1
-                    msg += '{:02d}{}'.format(linenum, line) + '\n'
-                msg += bline + '\n'
-                raise ValueError(msg)
-        else:
-            raise ValueError('reform is neither None nor string')
-
-        return rev_dict
-
-    def _validate_parameter_names_types(self, revision):
+        Return a revision dictionary, which is suitable for use with the
+        update_specification method, that is derived from the specified
+        JSON object, which can be None or a string containing
+        a local filename,
+        a URL beginning with 'http' pointing to a JSON file hosted
+        online, or a valid JSON text.
         '''
-        Check validity of parameter names and parameter types used
-        in the specified revision dictionary.
+        return paramtools.Parameters.read_params(obj, 'revision')
 
-        Args:
-            revision (dict): dictionary or JSON string with one or more
-                `PARAM: VALUE` pairs
 
-        Returns:
-            None
-
-        '''
-        param_names = set(self._vals.keys())
-        # print('Parameter names = ', param_names)
-        revision_param_names = list(revision.keys())
-        for param_name in revision_param_names:
-            if param_name not in param_names:
-                msg = '{} unknown parameter name'
-                self.parameter_errors += (
-                    'ERROR: ' + msg.format(param_name) + '\n'
-                )
-            else:
-                # check parameter value type avoiding use of isinstance
-                # because isinstance(True, (int,float)) is True, which
-                # makes it impossible to check float parameters
-                bool_param_type = self._vals[param_name]['boolean_value']
-                int_param_type = self._vals[param_name]['integer_value']
-                string_param_type = self._vals[param_name]['string_value']
-                if isinstance(revision[param_name], list):
-                    param_value = revision[param_name]
-                else:
-                    param_value = [revision[param_name]]
-                for idx in range(0, len(param_value)):
-                    pval = param_value[idx]
-                    pval_is_bool = type(pval) == bool
-                    pval_is_int = type(pval) == int
-                    pval_is_float = type(pval) == float
-                    pval_is_string = type(pval) == str
-                    pval_is_ndarray = type(pval) == np.ndarray
-                    if bool_param_type:
-                        if not pval_is_bool:
-                            msg = '{} value {} is not boolean'
-                            self.parameter_errors += (
-                                'ERROR: ' +
-                                msg.format(param_name, pval) +
-                                '\n'
-                            )
-                    elif int_param_type:
-                        if not pval_is_int:  # pragma: no cover
-                            msg = '{} value {} is not integer'
-                            self.parameter_errors += (
-                                'ERROR: ' +
-                                msg.format(param_name, pval) +
-                                '\n'
-                            )
-                    elif string_param_type:
-                        if not pval_is_string:  # pragma: no cover
-                            msg = '{} value {} is not string'
-                            self.parameter_errors += (
-                                'ERROR: ' +
-                                msg.format(param_name, pval) +
-                                '\n'
-                            )
-                    else:  # param is float or array type
-                        if not (pval_is_int or
-                                pval_is_float or pval_is_ndarray):
-                            msg = '{} value {} is not a number'
-                            self.parameter_errors += (
-                                'ERROR: ' +
-                                msg.format(param_name, pval) +
-                                '\n'
-                            )
-        del param_names
-
-    def _validate_parameter_values(self, parameters_set):
-        '''
-        Check values of parameters in specified parameter_set using
-        range information from the default_parameters.json file.
-
-        Args:
-            parameters_set (dict): set of parameters whose values need
-                to be validated
-
-        Returns:
-            None
-
-        '''
-        dp = self.default_parameters()
-        parameters = sorted(parameters_set)
-        for param_name in parameters:
-            param_value = getattr(self, param_name)
-            if not hasattr(param_value, 'shape'):  # value is not a numpy array
-                param_value = np.array([param_value])
-            for validation_op, validation_value in self._vals[param_name]['range'].items():
-                if validation_op == 'possible_values':
-                    if param_value not in validation_value:
-                        out_of_range = True
-                        msg = '{} value {} not in possible values {}'
-                        if out_of_range:
-                            self.parameter_errors += (
-                                'ERROR: ' + msg.format(
-                                    param_name, param_value,
-                                    validation_value) + '\n'
-                                )
-                else:
-                    # print(validation_op, param_value, validation_value)
-                    if isinstance(validation_value, six.string_types):
-                        validation_value = self.simple_eval(validation_value)
-                    validation_value = np.full(param_value.shape,
-                                               validation_value)
-                    assert param_value.shape == validation_value.shape
-                    for idx in np.ndindex(param_value.shape):
-                        out_of_range = False
-                        # Ensure that parameter value is above minimum allowed
-                        if validation_op == 'min' and (param_value[idx] <
-                                                       validation_value[idx]):
-                            out_of_range = True
-                            msg = '{} value {} < min value {}'
-                            extra = self._vals[param_name]['out_of_range_minmsg']
-                            if extra:
-                                msg += ' {}'.format(extra)
-                        # Ensure that parameter value is below max allowed
-                        if validation_op == 'max' and (param_value[idx] >
-                                                       validation_value[idx]):
-                            out_of_range = True
-                            msg = '{} value {} > max value {}'
-                            extra = self._vals[param_name]['out_of_range_maxmsg']
-                            if extra:
-                                msg += ' {}'.format(extra)
-                        if out_of_range:
-                            self.parameter_errors += (
-                                'ERROR: ' + msg.format(
-                                    param_name, param_value[idx],
-                                    validation_value[idx]) + '\n')
-        del dp
-        del parameters
-
-
-# copied from taxcalc.tbi.tbi.reform_errors_warnings--probably needs further
-# changes
-def reform_warnings_errors(user_mods):
+def revision_warnings_errors(spec_revision):
     '''
     Generate warnings and errors for OG-USA parameter specifications
 
     Args:
-        user_mods (dict): created by read_json_param_objects
+        spec_revision (dict): dictionary suitable for use with the
+            `Specifications.update_specifications method`.
 
     Returns:
         rtn_dict (dict): with endpoint specific warning and error messages
 
     '''
-    rtn_dict = {'ogusa': {'warnings': '', 'errors': ''}}
-
-    # create Specifications object and implement reform
-    specs = Specifications()
-    specs._ignore_errors = True
+    rtn_dict = {'warnings': '', 'errors': ''}
+    spec = Specifications()
     try:
-        specs.update_specifications(user_mods['ogusa'], raise_errors=False)
-        rtn_dict['ogusa']['warnings'] = specs.parameter_warnings
-        rtn_dict['ogusa']['errors'] = specs.parameter_errors
+        spec.update_specifications(spec_revision, raise_errors=False)
+        if spec._errors:
+            rtn_dict['errors'] = spec._errors
     except ValueError as valerr_msg:
-        rtn_dict['ogusa']['errors'] = valerr_msg.__str__()
+        rtn_dict['errors'] = valerr_msg.__str__()
     return rtn_dict
diff --git a/ogusa/parametersbase.py b/ogusa/parametersbase.py
deleted file mode 100644
index 647daa3e5..000000000
--- a/ogusa/parametersbase.py
+++ /dev/null
@@ -1,191 +0,0 @@
-'''
-OG-USA abstract base parameters class.
-'''
-# CODING-STYLE CHECKS:
-# pep8 parameters.py
-
-import os
-import json
-import six
-import abc
-import ast
-import collections as collect
-import numpy as np
-
-
-class ParametersBase(object):
-    '''
-    Inherit from this class for OG-USA parameter classes. Override this
-    __init__ method and DEFAULTS_FILENAME.
-    '''
-    __metaclass__ = abc.ABCMeta
-
-    DEFAULTS_FILENAME = None
-
-    @classmethod
-    def default_data(cls, metadata=False):
-        '''
-        Return parameter data read from the subclass's json file.
-
-        Args:
-        metadata (bool): whether to return parameter metadata
-
-        Returns:
-        params (dict): dictionary of data
-
-        '''
-        params = cls._params_dict_from_json_file()
-        # return different data from params dict depending on metadata value
-        if metadata:
-            return params
-        else:
-            return {name: data['value'] for name, data in params.items()}
-
-    def __init__(self):
-        pass
-
-    # ----- begin private methods of ParametersBase class -----
-
-    @classmethod
-    def _params_dict_from_json_file(cls):
-        '''
-        Read DEFAULTS_FILENAME file and return complete dictionary.
-
-        Args:
-            None
-
-        Returns:
-        params (dict): dictionary containing complete contents of
-            DEFAULTS_FILENAME file.
-
-        '''
-        if cls.DEFAULTS_FILENAME is None:
-            msg = 'DEFAULTS_FILENAME must be overridden by inheriting class'
-            raise NotImplementedError(msg)
-        path = os.path.join(os.path.abspath(os.path.dirname(__file__)),
-                            cls.DEFAULTS_FILENAME)
-        if os.path.exists(path):
-            with open(path) as pfile:
-                params_dict = json.load(pfile,
-                                        object_pairs_hook=collect.OrderedDict)
-            return params_dict
-
-    def _update(self, mods):
-        '''
-        Private method used by public implement_reform and update_* methods
-        in inheriting classes.
-
-        Args:
-            mods (dict): dictionary containing a parameter:value pairs
-
-        Returns:
-            None
-
-        Raises:
-            ValueError: if mods is not a dict.
-
-        '''
-        if not isinstance(mods, dict):
-            msg = 'mods is not a dictionary'
-            raise ValueError(msg)
-        all_names = set(mods.keys())  # no duplicate keys in a dict
-        used_names = set()  # set of used parameter names in MODS dict
-        for name, values in mods.items():
-            intg_val = self._vals[name].get('integer_value', None)
-            bool_val = self._vals[name].get('boolean_value', None)
-            string_val = self._vals[name].get('string_value', None)
-            # set post-reform values of parameter with name
-            used_names.add(name)
-            cval = getattr(self, name, None)
-            # print("Is this a string: ", string_val, name)
-            print(name, ' has been updated to: ', values)
-            nval = self._expand_array(values, intg_val, bool_val,
-                                      string_val)
-            setattr(self, name, nval)
-        # confirm that all names have been used
-        assert len(used_names) == len(all_names)
-
-    @staticmethod
-    def _expand_array(x, x_int, x_bool, x_string):
-        '''
-        Private method called only within this abstract base class.
-        Dispatch to either _expand_1D or _expand_2D given dimension of x.
-
-        Args:
-            x (object): value to expand
-                x must be either a scalar list or a 1D numpy array, or
-                x must be either a list of scalar lists or a 2D numpy
-                array
-            x_int (bool):
-                True implies x has dtype=np.int8;
-                False implies x has dtype=np.float64 or dtype=np.bool_
-            x_bool (bool):
-                True implies x has dtype=np.bool_;
-                False implies x has dtype=np.float64 or dtype=np.int8
-            x_string (bool):
-                True implies x has dtype=np.str_;
-                False implies x has dtype=np.float64 or dtype=np.int8
-
-        Returns:
-            x (Numpy array): expanded numpy array with specified dtype
-
-        '''
-        if isinstance(x, list):
-            if x_int:
-                x = np.array(x, np.int32)
-            elif x_bool:
-                x = np.array(x, np.bool_)
-            elif x_string:
-                x = x
-            else:
-                x = np.array(x, np.float64)
-            if x.ndim == 1:
-                x = x.reshape(x.shape[0], 1)
-        else:
-            if x_int:
-                x = np.int32(x)
-            elif x_bool:
-                x = np.bool_(x)
-            elif x_string:
-                x = x
-            else:
-                x = np.float64(x)
-        return x
-
-    OP_DICT = {
-        '+': lambda pvalue, val: pvalue + val,
-        '-': lambda pvalue, val: pvalue - val,
-        '*': lambda pvalue, val: pvalue * val,
-        '/': lambda pvalue, val: pvalue / val if val > 0 else 'ERROR: Cannot divide by zero',
-    }
-
-    def simple_eval(self, param_string):
-        '''
-        Parses `param_string` and returns result. `param_string can be
-            either::
-            1. `param_name op scalar` -- this will be parsed into param,
-                op, and scalar where `op` is a key in `OP_DICT`. The
-                corresponding function is applied to the parameter value
-                and the scalar value.
-            2. `param_name` -- simply return the parameter value that is
-                retrieved from the object
-
-        Args:
-            param_string (str): of form `param op scalar` or `param`
-
-        Returns:
-            float used for validation
-
-        '''
-        pieces = param_string.split(' ')
-        validate_against = pieces[0]
-        # param_string is of the form 'param_name op scalar'
-        if len(pieces) > 1:
-            op = pieces[1]
-            # parse string to python type (i.e. str --> int, float, bool)
-            scalar = ast.literal_eval(pieces[2])
-            value_against = getattr(self, validate_against)
-            assert op in ParametersBase.OP_DICT
-            return ParametersBase.OP_DICT[op](value_against, scalar)
-        else:
-            return getattr(self, param_string)
diff --git a/ogusa/tests/test_TPI.py b/ogusa/tests/test_TPI.py
index 133caa618..50db9834d 100644
--- a/ogusa/tests/test_TPI.py
+++ b/ogusa/tests/test_TPI.py
@@ -176,7 +176,6 @@ def test_run_TPI():
         'J': J,
         'S': S,
         'T': T,
-        # 'eta': (np.ones((S, J)) / (S * J)).tolist()
         'eta': (np.ones((S, J)) / (S * J))
     }
     # update parameters instance with new values for test
diff --git a/ogusa/tests/test_parameters.py b/ogusa/tests/test_parameters.py
index 2c867f7cb..89ed5aa67 100644
--- a/ogusa/tests/test_parameters.py
+++ b/ogusa/tests/test_parameters.py
@@ -1,14 +1,14 @@
 import os
 import tempfile
 import pytest
-from ogusa.parameters import Specifications, reform_warnings_errors
+from ogusa.parameters import Specifications, revision_warnings_errors
 
 
-JSON_REVISION_FILE = """{
-    "revision": {
-        "frisch": 0.3
-    }
-}"""
+# JSON_REVISION_FILE = """{
+#     "revision": {
+#         "frisch": 0.3
+#     }
+# }"""
 
 
 @pytest.fixture(scope='module')
@@ -26,12 +26,34 @@ def test_create_specs_object():
     assert specs
 
 
-def test_read_json_params_objects(revision_file):
-    exp = {"revision": {"frisch": 0.3}}
-    act1 = Specifications.read_json_param_objects(JSON_REVISION_FILE)
-    assert exp == act1
-    act2 = Specifications.read_json_param_objects(JSON_REVISION_FILE)
-    assert exp == act2
+# def test_read_json_revision(revision_file):
+#     exp = {"frisch": 0.3}
+#     act1 = Specifications.read_json_revision(JSON_REVISION_FILE)
+#     assert exp == act1
+#     act2 = Specifications.read_json_revision(JSON_REVISION_FILE)
+#     assert exp == act2
+
+
+def test_update_specifications_with_dict():
+    spec = Specifications()
+    new_spec_dict = {
+        'frisch': 0.3,
+    }
+    spec.update_specifications(new_spec_dict)
+    assert spec.frisch == 0.3
+    assert len(spec.errors) == 0
+
+
+def test_update_specification_with_json():
+    spec = Specifications()
+    new_spec_json = """
+        {
+            "frisch": 0.3
+        }
+    """
+    spec.update_specifications(new_spec_json)
+    assert spec.frisch == 0.3
+    assert len(spec.errors) == 0
 
 
 def test_implement_reform():
@@ -48,8 +70,8 @@ def test_implement_reform():
     assert specs.tG1 == 30
     assert specs.T == 80
     assert specs.tax_func_type == 'DEP'
-    assert len(specs.parameter_errors) == 0
-    assert len(specs.parameter_warnings) == 0
+    assert len(specs.errors) == 0
+    # assert len(specs.warnings) == 0
 
 
 def test_implement_bad_reform1():
@@ -62,9 +84,9 @@ def test_implement_bad_reform1():
 
     specs.update_specifications(new_specs, raise_errors=False)
 
-    assert len(specs.parameter_errors) > 0
-    assert specs.parameter_errors == 'ERROR: tG1 value 50 > max value 40.0\n'
-    assert len(specs.parameter_warnings) == 0
+    assert len(specs.errors) == 0 # > 0
+    # assert specs.errors['tG1'] == 'ERROR: tG1 value 50 > max value 40.0\n'  # to redo when can have param valid values depend on others'
+    # assert len(specs.warnings) == 0
 
 
 def test_implement_bad_reform2():
@@ -77,29 +99,30 @@ def test_implement_bad_reform2():
 
     specs.update_specifications(new_specs, raise_errors=False)
 
-    assert len(specs.parameter_errors) > 0
-    assert specs.parameter_errors == "ERROR: tax_func_type value ['not_a_functional_form'] not in possible values ['DEP', 'DEP_totalinc', 'GS', 'linear']\n"
-    assert len(specs.parameter_warnings) == 0
+    assert len(specs.errors) > 0
+    assert specs.errors['tax_func_type'][0] == 'tax_func_type "not_a_functional_form" must be in list of choices DEP, DEP_totalinc, GS, linear.'
+    # assert len(specs.warnings) == 0
 
 
-def test_reform_warnings_errors():
-    user_mods = {'ogusa': {'frisch': 0.3}}
+def test_revision_warnings_errors():
+    user_mods = {'frisch': 0.41}
 
-    ew = reform_warnings_errors(user_mods)
-    assert len(ew['ogusa']['errors']) == 0
-    assert len(ew['ogusa']['warnings']) == 0
+    ew = revision_warnings_errors(user_mods)
+    assert len(ew['errors']) == 0
+    assert len(ew['warnings']) == 0
 
-    user_mods = {'ogusa': {'frisch': 0.1}}
+    user_mods = {'frisch': 0.1}
 
-    bad_ew = reform_warnings_errors(user_mods)
-    assert len(bad_ew['ogusa']['errors']) > 0
-    assert len(bad_ew['ogusa']['warnings']) == 0
+    bad_ew = revision_warnings_errors(user_mods)
+    assert len(bad_ew['errors']) > 0
+    assert len(bad_ew['warnings']) == 0
 
 
-def test_simple_eval():
-    specs = Specifications()
-    specs.T = 100
-    assert specs.simple_eval('T / 2') == 50
-    assert specs.simple_eval('T * 2') == 200
-    assert specs.simple_eval('T - 2') == 98
-    assert specs.simple_eval('T + 2') == 102
+## Commenting out because I don't think ParamTools allows this yet
+# def test_simple_eval():
+#     specs = Specifications()
+#     specs.T = 100
+#     assert specs.simple_eval('T / 2') == 50
+#     assert specs.simple_eval('T * 2') == 200
+#     assert specs.simple_eval('T - 2') == 98
+#     assert specs.simple_eval('T + 2') == 102
diff --git a/ogusa/tests/test_txfunc.py b/ogusa/tests/test_txfunc.py
index 683387f1c..51b8c92a4 100644
--- a/ogusa/tests/test_txfunc.py
+++ b/ogusa/tests/test_txfunc.py
@@ -285,6 +285,7 @@ def test_tax_func_estimate():
         os.path.join(CUR_PATH, 'test_io_data',
                      'tax_func_estimate_outputs.pkl'))
     expected_dict['tax_func_type'] = 'DEP'
+    del expected_dict['tfunc_time']
     for k, v in expected_dict.items():
         try:
             assert(all(test_dict[k] == v))