diff --git a/docs/source/change-log.rst b/docs/source/change-log.rst
index 4ca6029..abdcf2d 100644
--- a/docs/source/change-log.rst
+++ b/docs/source/change-log.rst
@@ -10,6 +10,31 @@ This project adheres to `Semantic Versioning`_.
 
 .. _Semantic Versioning: http://semver.org/
 
+
+0.7.0
+-----
+2025-06-09
+
+* New Features
+
+  * Support for IPUMS IHGIS extract API, including
+
+    * Support for IPUMS IHGIS has been added to :py:class:`~ipumspy.api.extract.AggregateDataExtract`
+    * :py:class:`~ipumspy.api.extract.IhgisDataset` added for use when constructing IPUMS IHGIS extract requests.
+  
+  * Support for IPUMS IHGIS metadata API, including
+
+    * :py:class:`~ipumspy.api.metadata.IhgisDatasetMetadata`
+    * :py:class:`~ipumspy.api.metadata.IhgisDataTableMetadata`
+
+  * Support for the Monetary Value Adjustment feature on select variables from IPUMS USA and IPUMS CPS
+
+* Breaking Changes
+
+  * :py:class:`~ipumspy.api.extract.Dataset` has been renamed :py:class:`~ipumspy.api.extract.NhgisDataset`
+  * :py:class:`~ipumspy.api.metadata.DatasetMetadata` has been renamed :py:class:`~ipumspy.api.metadata.NhgisDatasetMetadata`
+  * :py:class:`~ipumspy.api.metadata.DataTableMetadata` has been renamed :py:class:`~ipumspy.api.metadata.NhgisDatasetMetadata`
+
 0.6.2
 -----
 2025-04-18
diff --git a/docs/source/ipums_api/index.rst b/docs/source/ipums_api/index.rst
index dbfa3c9..15405ec 100644
--- a/docs/source/ipums_api/index.rst
+++ b/docs/source/ipums_api/index.rst
@@ -88,6 +88,11 @@ available features for all collections currently supported by the API:
       - ``nhgis``
       - **X**
       - **X**
+    * - `IPUMS IHGIS <https://ihgis.ipums.org/>`__
+      - Aggregate data
+      - ``ihgis``
+      - **X**
+      - **X**
 
 Note that ipumspy may not necessarily support all the functionality currently supported by
 the IPUMS API. See the `API documentation <https://developer.ipums.org/>`__ for more information 
@@ -195,29 +200,44 @@ metadata obtained for the requested data source:
   tst.description
   #> 'Total Population'
 
-The following table summarizes the currently available metadata endpoints:
+The following table summarizes the currently available metadata endpoints. Endpoints listed
+in the **Metadata type** column can be used with the indicated collection in :py:meth:`.get_metadata_catalog`.
+Classes listed in the **Detailed metadata class** column can be used to obtain detailed metadata for
+individual data sources of that type.
 
 .. _metadata support table:
 
 .. list-table:: Supported metadata endpoints
-    :widths: 2 3 5
+    :widths: 3 2 5
     :header-rows: 1
     :align: center
 
-    * - Metadata type
-      - Supported collections
-      - Detailed metadata class analog
-    * - ``datasets``
-      - IPUMS NHGIS
-      - :py:class:`~ipumspy.api.metadata.DatasetMetadata`
-    * - ``data_tables``
-      - IPUMS NHGIS
-      - :py:class:`~ipumspy.api.metadata.DataTableMetadata`
-    * - ``time_series_tables``
-      - IPUMS NHGIS
+    * - Collection
+      - Metadata type
+      - Detailed metadata class
+    * - NHGIS
+      - ``datasets``
+      - :py:class:`~ipumspy.api.metadata.NhgisDatasetMetadata`
+    * - NHGIS
+      - ``data_tables``
+      - :py:class:`~ipumspy.api.metadata.NhgisDataTableMetadata`
+    * - NHGIS
+      - ``time_series_tables``
       - :py:class:`~ipumspy.api.metadata.TimeSeriesTableMetadata`
-    * - ``shapefiles``
-      - IPUMS NHGIS
+    * - NHGIS
+      - ``shapefiles``
+      -
+    * -
+      -
+      -
+    * - IHGIS
+      - ``datasets``
+      - :py:class:`~ipumspy.api.metadata.IhgisDatasetMetadata`
+    * - IHGIS
+      - ``data_tables``
+      - :py:class:`~ipumspy.api.metadata.IhgisDataTableMetadata`
+    * - IHGIS
+      - ``tabulation_geographies``
       -
 
 .. _submit-extract:
diff --git a/docs/source/ipums_api/ipums_api_aggregate/index.rst b/docs/source/ipums_api/ipums_api_aggregate/index.rst
index 1aa57d8..03e1b78 100644
--- a/docs/source/ipums_api/ipums_api_aggregate/index.rst
+++ b/docs/source/ipums_api/ipums_api_aggregate/index.rst
@@ -6,9 +6,25 @@ Aggregate Data Extracts
 =======================
 
 IPUMS aggregate data collections distribute aggregated statistics for a set of geographic units.
+IPUMS contains two aggregate data collections, both of which are supported by the IPUMS API:
 
-Currently, `IPUMS NHGIS <https://www.nhgis.org/>`__ is the only aggregate data collection
-supported by the IPUMS API.
+-  `IPUMS NHGIS <https://www.nhgis.org/>`__
+-  `IPUMS IHGIS <https://www.ihgis.ipums.org>`__
+
+IPUMS NHGIS provides 3 different types of data sources:
+
+- Datasets/data tables
+- Time series tables
+- Shapefiles
+
+IPUMS IHGIS provides 1 type of data source:
+
+- Datasets/data tables
+
+.. note::
+   IHGIS does provide boundary shapefiles, but these are not provided 
+   via the IPUMS API. Shapefiles from IHGIS can be downloaded directly from the 
+   `IHGIS website <https://ihgis.ipums.org/geography-gis>`__.
 
 Extract Objects
 ---------------
@@ -16,26 +32,20 @@ Extract Objects
 Construct an extract for an IPUMS aggregate data collection using the 
 :class:`AggregateDataExtract<ipumspy.api.extract.AggregateDataExtract>` class.
 An ``AggregateDataExtract`` must contain an IPUMS collection ID 
-and at least one data source. IPUMS NHGIS provides 3 different types of data sources:
-
-- Datasets/data tables
-- Time series tables
-- Shapefiles
-
-We also recommend providing an extract description to make it easier to identify and 
-retrieve your extract in the future.
+and at least one data source. We also recommend providing an extract description
+to make it easier to identify and retrieve your extract in the future.
 
 For example:
 
 .. code:: python
 
-   from ipumspy import AggregateDataExtract, Dataset
+   from ipumspy import AggregateDataExtract, NhgisDataset
 
    extract = AggregateDataExtract(
       collection="nhgis",
       description="An NHGIS extract example",
       datasets=[
-         Dataset(name="1990_STF1", data_tables=["NP1", "NP2"], geog_levels=["county"])
+         NhgisDataset(name="1990_STF1", data_tables=["NP1", "NP2"], geog_levels=["county"])
       ]
    )
 
@@ -48,9 +58,7 @@ After instantiation, an ``AggregateDataExtract`` object can be
 
 .. note::
    The IPUMS API provides a set of metadata endpoints for aggregate data collections that allow you
-   to browse available data sources and identify their associated API codes.
-
-   You can also browse metadata interactively through the `NHGIS Data Finder <https://data2.nhgis.org/main>`_.
+   to browse available data sources and identify their associated API codes (see below for examples).
 
 Datasets + Data Tables
 ----------------------
@@ -59,12 +67,17 @@ An IPUMS **dataset** contains a collection of **data tables** that each correspo
 A dataset is distinguished by the years, geographic levels, and topics that it covers. For instance, 2021 1-year data from the 
 American Community Survey (ACS) is encapsulated in a single dataset. In other cases, a single census product will be split into 
 multiple datasets, typically based on the lowest-level geography for which a set of tables is available. See the 
-`NHGIS documentation <https://www.nhgis.org/overview-nhgis-datasets>`_ for more details.
+`NHGIS <https://www.nhgis.org/overview-nhgis-datasets>`_ and `IHGIS <https://ihgis.ipums.org/dataset-descriptions>`__ documentation
+for more details.
 
 To request data contained in an IPUMS dataset, you need to specify the name of the dataset, name of the data table(s) to request
-from that dataset, and the geographic level at which those tables should be aggregated.
+from that dataset, and the geographic level at which those tables should be aggregated. 
+
+NHGIS Datasets
+++++++++++++++
 
-Use the :class:`Dataset <ipumspy.api.extract.Dataset>` class to specify these parameters.
+For NHGIS extracts, use the
+:class:`NhgisDataset <ipumspy.api.extract.NhgisDataset>` class to specify these parameters:
 
 .. code:: python
 
@@ -72,7 +85,7 @@ Use the :class:`Dataset <ipumspy.api.extract.Dataset>` class to specify these pa
       collection="nhgis",
       description="An NHGIS example extract",
       datasets=[
-         Dataset(name="2000_SF1a", data_tables=["NP001A", "NP031A"], geog_levels=["state"])
+         NhgisDataset(name="2000_SF1a", data_tables=["NP001A", "NP031A"], geog_levels=["state"])
       ],
    )
 
@@ -84,7 +97,7 @@ Some datasets span multiple years and require a selection of ``years``:
       collection="nhgis",
       description="An NHGIS example extract",
       datasets=[
-         Dataset(
+         NhgisDataset(
             name="1988_1997_CBPa",
             data_tables=["NT004"],
             geog_levels=["county"],
@@ -105,7 +118,7 @@ for a dataset with the ``breakdown_values`` keyword argument:
       collection="nhgis",
       description="An NHGIS example extract",
       datasets=[
-         Dataset(
+         NhgisDataset(
                name="2000_SF1a",
                data_tables=["NP001A", "NP031A"],
                geog_levels=["state"],
@@ -122,23 +135,49 @@ For datasets with multiple breakdowns or data types (e.g., the American Communit
 and margins of error), you can request that the data for each be provided in separate files or together in a
 single file using the ``breakdown_and_data_type_layout`` argument.
 
+IHGIS Datasets
+++++++++++++++
+
+For IHGIS, each dataset must be associated with a selection of data tables and tabulation geographies
+(the level of geographic aggregation for the requested data). These are the only available parameters
+for IHGIS dataset requests.
+
+.. code:: python
+
+   AggregateDataExtract(
+      collection="ihgis",
+      description="An IHGIS example extract",
+      datasets=[
+         IhgisDataset(
+            "KZ2009pop", 
+            data_tables=["KZ2009pop.AAA"], 
+            tabulation_geographies=["KZ2009pop.g0"]
+         )
+      ]
+   )
+
+.. caution::
+   IHGIS extract requests only accept input for ``description`` and ``datasets``. Other ``AggregateDataExtract``
+   arguments do not apply to IHGIS extracts and will be omitted from the extract request if included.
+
 Dataset + Data Table Metadata
 +++++++++++++++++++++++++++++
 
 You can obtain a listing of datasets and data tables as well as detailed information about individual
 datasets and data tables via the :ref:`IPUMS Metadata API <ipums-metadata>`.
 
-Use the :class:`DatasetMetadata <ipumspy.api.metadata.DatasetMetadata>` data class to browse the available
-specification options for a particular dataset and identify the codes to use when
-requesting data from the API:
+Use the :class:`NhgisDatasetMetadata <ipumspy.api.metadata.NhgisDatasetMetadata>` and 
+:class:`IhgisDatasetMetadata <ipumspy.api.metadata.IhgisDatasetMetadata>` data classes
+to browse the available specification options for a particular dataset and identify 
+the codes to use when requesting data from the API:
 
 .. code:: python
 
-   from ipumspy import IpumsApiClient, DatasetMetadata
+   from ipumspy import IpumsApiClient, NhgisDatasetMetadata
 
    ipums = IpumsApiClient(os.environ.get("IPUMS_API_KEY"))
 
-   ds = ipums.get_metadata(DatasetMetadata("nhgis", "2000_SF1a"))
+   ds = ipums.get_metadata(NhgisDatasetMetadata("2000_SF1a"))
 
 The returned object will contain the metadata for the requested dataset. For example:
 
@@ -152,7 +191,9 @@ The returned object will contain the metadata for the requested dataset. For exa
 
    # etc...
 
-You can also request metadata for individual data tables using the same workflow with the :class:`DataTableMetadata <ipumspy.api.metadata.DataTableMetadata>` data class.
+You can also request metadata for individual data tables using the same workflow with the
+:class:`NhgisDataTableMetadata <ipumspy.api.metadata.NhgisDataTableMetadata>` and
+:class:`IhgisDataTableMetadata <ipumspy.api.metadata.IhgisDataTableMetadata>` data classes.
 
 Time Series Tables
 ------------------
@@ -162,7 +203,7 @@ U.S. censuses in a single package. A table is comprised of one or more related t
 of which describes a single summary statistic measured at multiple times for a given geographic level.
 
 Use the :class:`TimeSeriesTable<ipumspy.api.extract.TimeSeriesTable>` class to add time series tables
-to your extract request.
+to your NHGIS extract request.
 
 Time series tables are already associated with a specific summary statistic, so they don't require an additional
 selection of data tables as is required for NHGIS datasets. However, you will need to specify the geographic
@@ -218,7 +259,7 @@ Geographic Extent Selection
 
 When working with small geographies it can be computationally intensive to work with
 nationwide data. To avoid this problem, you can request data from a specific geographic area 
-using the ``geographic_extents`` argument
+using the ``geographic_extents`` argument. This argument is only available for NHGIS extracts.
 
 The following extract requests ACS 5-year sex-by-age counts at the census block group level, but
 only includes block groups that fall within Alabama and Arkansas (identified by their FIPS codes with
@@ -230,15 +271,15 @@ a trailing 0):
       collection="nhgis",
       description="Extent selection example",
       datasets=[
-         Dataset(name="2018_2022_ACS5a", data_tables=["B01001"], geog_levels=["blck_grp"]),
-         Dataset(name="2017_2021_ACS5a", data_tables=["B01001"], geog_levels=["blck_grp"])
+         NhgisDataset(name="2018_2022_ACS5a", data_tables=["B01001"], geog_levels=["blck_grp"]),
+         NhgisDataset(name="2017_2021_ACS5a", data_tables=["B01001"], geog_levels=["blck_grp"])
       ],
       geographic_extents=["010", "050"]
    )
 
 .. tip::
    You can see available extent selection API codes, if any, in the ``geographic_instances`` attribute of
-   a submitted :class:`DatasetMetadata <ipumspy.api.metadata.DatasetMetadata>` or 
+   a submitted :class:`NhgisDatasetMetadata <ipumspy.api.metadata.NhgisDatasetMetadata>` or 
    :class:`TimeSeriesTableMetadata <ipumspy.api.metadata.TimeSeriesTableMetadata>` object. The 
    ``geog_levels`` attribute indicates whether a given geographic level supports extent selection.
 
@@ -261,6 +302,8 @@ simply by specifying their names:
       shapefiles=["us_county_2021_tl2021", "us_county_2020_tl2020"]
    )
 
+As mentioned above, IHGIS shapefiles must be downloaded directly from the `IHGIS website <https://ihgis.ipums.org/geography-gis>`__.
+
 Shapefile Metadata
 ++++++++++++++++++
 
@@ -282,8 +325,8 @@ datasets:
       collection="nhgis",
       description="An NHGIS example extract",
       datasets=[
-         Dataset(name="2000_SF1a", data_tables=["NP001A"], geog_levels=["state"]),
-         Dataset(name="2010_SF1a", data_tables=["P1"], geog_levels=["state"])
+         NhgisDataset(name="2000_SF1a", data_tables=["NP001A"], geog_levels=["state"]),
+         NhgisDataset(name="2010_SF1a", data_tables=["P1"], geog_levels=["state"])
       ],
       shapefiles=["us_state_2000_tl2010", "us_state_2010_tl2010"]
    )
@@ -296,7 +339,7 @@ several ACS years at once using list comprehensions. For instance:
 
    acs1_names = ["2017_ACS1", "2018_ACS1", "2019_ACS1"]
    acs1_specs = [
-      Dataset(name, data_tables=["B01001"], geog_levels=["state"]) for name in acs1_names
+      NhgisDataset(name, data_tables=["B01001"], geog_levels=["state"]) for name in acs1_names
    ]
 
    # Total state-level population from 2017-2019 ACS 1-year estimates
@@ -313,8 +356,10 @@ By default, NHGIS extracts are provided in CSV format with only a single header
 If you like, you can request that your CSV data include a second header row containing
 a description of each column's contents by setting ``data_format="csv_header"``.
 
-You can also request your data in
-fixed-width format if so desired. Note that unlike for microdata projects, NHGIS does
+While you can also request your data in
+fixed-width format, NHGIS is likely to phase out support for this format in the
+future. We therefore suggest that you request data in CSV format.
+Also note that unlike for microdata projects, NHGIS does
 not provide DDI codebook files (in XML format), which allow ipumspy to parse
 microdata fixed-width files. Thus, loading an NHGIS fixed width file will require
 manual work to parse the file correctly.
diff --git a/docs/source/ipums_api/ipums_api_micro/index.rst b/docs/source/ipums_api/ipums_api_micro/index.rst
index d431d11..dc0f9fe 100644
--- a/docs/source/ipums_api/ipums_api_micro/index.rst
+++ b/docs/source/ipums_api/ipums_api_micro/index.rst
@@ -276,6 +276,26 @@ Data quality flags can also be selected for specific variables using the :meth:`
     # note that this method will also accept a list!
     extract.add_data_quality_flags(["AGE", "SEX"])
 
+Adjust Monetary Values
+~~~~~~~~~~~~~~~~~~~~~~
+
+IPUMS CPS and IPUMS USA offer the option to standardize income or other dollar values to 2010 dollars. This option both retains the original IPUMS variable in your extract and adds a new, adjusted variable called ``<VARIABLE NAME>_cpiu_2010`` that contains the inflation-adjusted values. Further information on the Adjust Monetary Values feature can be found on the `IPUMS CPS <https://cps.ipums.org/cps/adjusted_monetary_values.shtml>`_ and `IPUMS USA <https://usa.ipums.org/usa/adjusted_monetary_values.shtml>`_ websites.
+
+Inflation adjusted values are only available for continuous variables that represent dollar amounts and can be selected using the :meth:`.adjust_monetary_values()` method.
+
+.. code:: python
+
+    extract = MicrodataExtract(
+        collection="cps",
+        samples=["cps2022_03b"],
+        variables=["AGE", "SEX", "HOURWAGE"],
+    )
+
+    extract.adjust_monetary_values("HOURWAGE")
+
+.. note::
+    The Adjust Monetary Values feature is not currently available for IPUMS CPS ASEC variables.
+
 .. _Using Variable Objects to Include Extract Features:
 
 Variable Objects
@@ -286,8 +306,8 @@ defining a :class:`MicrodataExtract<ipumspy.api.extract.MicrodataExtract>` using
 :class:`Variable<ipumspy.api.extract.Variable>` objects. 
 
 The example below defines an IPUMS CPS extract that includes a variable for the age of 
-the spouse (``attached_characteristics``), limits the sample to women (``case_selections``), and includes the 
-data quality flag for RACE (``data_quality_flags``).
+the spouse (``attached_characteristics``), limits the sample to women (``case_selections``), includes the 
+data quality flag for RACE (``data_quality_flags``), and an inflation-adjusted version of INCTOT (``adjust_monetary_values``).
 
 .. code:: python
 
@@ -300,7 +320,9 @@ data quality flag for RACE (``data_quality_flags``).
             Variable(name="SEX",
                      case_selections={"general": ["2"]}),
             Variable(name="RACE",
-                     data_quality_flags=True)
+                     data_quality_flags=True),
+            Variable(name="HOURWAGE",
+                     adjust_monetary_values=True),
          ],
          description="A fancy CPS extract",
     )
diff --git a/docs/source/reading_data.rst b/docs/source/reading_data.rst
index 9e8fdb9..d8b5b76 100644
--- a/docs/source/reading_data.rst
+++ b/docs/source/reading_data.rst
@@ -136,11 +136,6 @@ pandas to load the compressed csv file:
         with z.open(names[0]) as f:
             data = pd.read_csv(f)
 
-.. note::
-    IPUMS NHGIS does allow you to request an extract in fixed-width format, but ipumspy does not
-    provide methods to parse these files as it does for Microdata because IPUMS NHGIS does not provide
-    the necessary DDI codebook.
-
 Shapefile data is delivered in a nested zipfile that can also be unpacked using the ``ZipFile`` module and read using third party libraries such as geopandas.
 
 Reading Non-Extractable IPUMS Collections
diff --git a/docs/source/reference/api.rst b/docs/source/reference/api.rst
index 53b8e1e..80e7661 100644
--- a/docs/source/reference/api.rst
+++ b/docs/source/reference/api.rst
@@ -44,7 +44,8 @@ Helpful data classes for defining IPUMS Extract objects.
    ipumspy.api.Variable
    ipumspy.api.Sample
    ipumspy.api.TimeUseVariable
-   ipumspy.api.Dataset
+   ipumspy.api.NhgisDataset
+   ipumspy.api.IhgisDataset
    ipumspy.api.TimeSeriesTable
    ipumspy.api.Shapefile
 
@@ -74,8 +75,10 @@ Use these classes and methods to request IPUMS metadata for aggregate data colle
    :template: class.rst
    :nosignatures:
 
-   ipumspy.api.metadata.DatasetMetadata
-   ipumspy.api.metadata.DataTableMetadata
+   ipumspy.api.metadata.NhgisDatasetMetadata
+   ipumspy.api.metadata.IhgisDatasetMetadata
+   ipumspy.api.metadata.NhgisDataTableMetadata
+   ipumspy.api.metadata.IhgisDataTableMetadata
    ipumspy.api.metadata.TimeSeriesTableMetadata
 
 Exceptions
diff --git a/poetry.lock b/poetry.lock
index 9de7f71..075a5b5 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -174,14 +174,14 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "certifi"
-version = "2025.1.31"
+version = "2025.4.26"
 description = "Python package for providing Mozilla's CA Bundle."
 category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"},
-    {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"},
+    {file = "certifi-2025.4.26-py3-none-any.whl", hash = "sha256:30350364dfe371162649852c63336a15c70c6510c2ad5015b21c2345311805f3"},
+    {file = "certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6"},
 ]
 
 [[package]]
@@ -198,104 +198,104 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.4.1"
+version = "3.4.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e218488cd232553829be0664c2292d3af2eeeb94b32bea483cf79ac6a694e037"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:80ed5e856eb7f30115aaf94e4a08114ccc8813e6ed1b5efa74f9f82e8509858f"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b010a7a4fd316c3c484d482922d13044979e78d1861f0e0650423144c616a46a"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4532bff1b8421fd0a320463030c7520f56a79c9024a4e88f01c537316019005a"},
-    {file = "charset_normalizer-3.4.1-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d973f03c0cb71c5ed99037b870f2be986c3c05e63622c017ea9816881d2dd247"},
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@@ -434,38 +438,42 @@ files = [
 
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+
 [package.extras]
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 [[package]]
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@@ -1076,14 +1084,14 @@ files = [
 
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+version = "25.0"
 description = "Core utilities for Python packages"
 category = "dev"
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 python-versions = ">=3.8"
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 [[package]]
@@ -1187,14 +1195,14 @@ files = [
 
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-version = "4.3.7"
+version = "4.3.8"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 category = "dev"
 optional = false
 python-versions = ">=3.9"
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@@ -1204,19 +1212,19 @@ type = ["mypy (>=1.14.1)"]
 
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+version = "1.6.0"
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 category = "dev"
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-python-versions = ">=3.8"
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 dev = ["pre-commit", "tox"]
-testing = ["pytest", "pytest-benchmark"]
+testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "propcache"
@@ -1383,19 +1391,19 @@ test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
 
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 typing-extensions = ">=4.12.2"
 typing-inspection = ">=0.4.0"
 
@@ -1405,111 +1413,111 @@ timezone = ["tzdata"]
 
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+    {file = "pydantic_core-2.33.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:2807668ba86cb38c6817ad9bc66215ab8584d1d304030ce4f0887336f28a5e27"},
+    {file = "pydantic_core-2.33.2.tar.gz", hash = "sha256:7cb8bc3605c29176e1b105350d2e6474142d7c1bd1d9327c4a9bdb46bf827acc"},
 ]
 
 [package.dependencies]
@@ -1773,26 +1781,26 @@ files = [
 
 [[package]]
 name = "snowballstemmer"
-version = "2.2.0"
-description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms."
+version = "3.0.1"
+description = "This package provides 32 stemmers for 30 languages generated from Snowball algorithms."
 category = "dev"
 optional = false
-python-versions = "*"
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*"
 files = [
-    {file = "snowballstemmer-2.2.0-py2.py3-none-any.whl", hash = "sha256:c8e1716e83cc398ae16824e5572ae04e0d9fc2c6b985fb0f900f5f0c96ecba1a"},
-    {file = "snowballstemmer-2.2.0.tar.gz", hash = "sha256:09b16deb8547d3412ad7b590689584cd0fe25ec8db3be37788be3810cbf19cb1"},
+    {file = "snowballstemmer-3.0.1-py3-none-any.whl", hash = "sha256:6cd7b3897da8d6c9ffb968a6781fa6532dce9c3618a4b127d920dab764a19064"},
+    {file = "snowballstemmer-3.0.1.tar.gz", hash = "sha256:6d5eeeec8e9f84d4d56b847692bacf79bc2c8e90c7f80ca4444ff8b6f2e52895"},
 ]
 
 [[package]]
 name = "soupsieve"
-version = "2.6"
+version = "2.7"
 description = "A modern CSS selector implementation for Beautiful Soup."
 category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "soupsieve-2.6-py3-none-any.whl", hash = "sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9"},
-    {file = "soupsieve-2.6.tar.gz", hash = "sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb"},
+    {file = "soupsieve-2.7-py3-none-any.whl", hash = "sha256:6e60cc5c1ffaf1cebcc12e8188320b72071e922c2e897f737cadce79ad5d30c4"},
+    {file = "soupsieve-2.7.tar.gz", hash = "sha256:ad282f9b6926286d2ead4750552c8a6142bc4c783fd66b0293547c8fe6ae126a"},
 ]
 
 [[package]]
@@ -1990,22 +1998,22 @@ test = ["pytest"]
 
 [[package]]
 name = "starlette"
-version = "0.36.3"
+version = "0.46.2"
 description = "The little ASGI library that shines."
 category = "dev"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "starlette-0.36.3-py3-none-any.whl", hash = "sha256:13d429aa93a61dc40bf503e8c801db1f1bca3dc706b10ef2434a36123568f044"},
-    {file = "starlette-0.36.3.tar.gz", hash = "sha256:90a671733cfb35771d8cc605e0b679d23b992f8dcfad48cc60b38cb29aeb7080"},
+    {file = "starlette-0.46.2-py3-none-any.whl", hash = "sha256:595633ce89f8ffa71a015caed34a5b2dc1c0cdb3f0f1fbd1e69339cf2abeec35"},
+    {file = "starlette-0.46.2.tar.gz", hash = "sha256:7f7361f34eed179294600af672f565727419830b54b7b084efe44bb82d2fccd5"},
 ]
 
 [package.dependencies]
-anyio = ">=3.4.0,<5"
+anyio = ">=3.6.2,<5"
 typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""}
 
 [package.extras]
-full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"]
+full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.18)", "pyyaml"]
 
 [[package]]
 name = "tomli"
@@ -2075,14 +2083,14 @@ files = [
 
 [[package]]
 name = "typing-inspection"
-version = "0.4.0"
+version = "0.4.1"
 description = "Runtime typing introspection tools"
 category = "dev"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "typing_inspection-0.4.0-py3-none-any.whl", hash = "sha256:50e72559fcd2a6367a19f7a7e610e6afcb9fac940c650290eed893d61386832f"},
-    {file = "typing_inspection-0.4.0.tar.gz", hash = "sha256:9765c87de36671694a67904bf2c96e395be9c6439bb6c87b5142569dcdd65122"},
+    {file = "typing_inspection-0.4.1-py3-none-any.whl", hash = "sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51"},
+    {file = "typing_inspection-0.4.1.tar.gz", hash = "sha256:6ae134cc0203c33377d43188d4064e9b357dba58cff3185f22924610e70a9d28"},
 ]
 
 [package.dependencies]
@@ -2119,14 +2127,14 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.34.1"
+version = "0.34.2"
 description = "The lightning-fast ASGI server."
 category = "dev"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "uvicorn-0.34.1-py3-none-any.whl", hash = "sha256:984c3a8c7ca18ebaad15995ee7401179212c59521e67bfc390c07fa2b8d2e065"},
-    {file = "uvicorn-0.34.1.tar.gz", hash = "sha256:af981725fc4b7ffc5cb3b0e9eda6258a90c4b52cb2a83ce567ae0a7ae1757afc"},
+    {file = "uvicorn-0.34.2-py3-none-any.whl", hash = "sha256:deb49af569084536d269fe0a6d67e3754f104cf03aba7c11c40f01aadf33c403"},
+    {file = "uvicorn-0.34.2.tar.gz", hash = "sha256:0e929828f6186353a80b58ea719861d2629d766293b6d19baf086ba31d4f3328"},
 ]
 
 [package.dependencies]
@@ -2588,14 +2596,14 @@ propcache = ">=0.2.1"
 
 [[package]]
 name = "zipp"
-version = "3.21.0"
+version = "3.22.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"},
-    {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"},
+    {file = "zipp-3.22.0-py3-none-any.whl", hash = "sha256:fe208f65f2aca48b81f9e6fd8cf7b8b32c26375266b009b413d45306b6148343"},
+    {file = "zipp-3.22.0.tar.gz", hash = "sha256:dd2f28c3ce4bc67507bfd3781d21b7bb2be31103b51a4553ad7d90b84e57ace5"},
 ]
 
 [package.extras]
@@ -2603,7 +2611,7 @@ check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
 cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 enabler = ["pytest-enabler (>=2.2)"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+test = ["big-O", "importlib_resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more_itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
 type = ["pytest-mypy"]
 
 [extras]
@@ -2612,4 +2620,4 @@ docs = []
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "dcf96220a9ced6d5031be7d2eddbe1415df89297f41848366e42d105eb55562f"
+content-hash = "0f7dfb98daffdd53ab296fe780eb6967f02b3c1408604ad8fd757ca54a3379ef"
diff --git a/pyproject.toml b/pyproject.toml
index 57193a2..ec2bd4b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ipumspy"
-version = "0.6.2"
+version = "0.7.0"
 description = "A collection of tools for working with IPUMS data"
 authors = ["Kevin H. Wilson <kevin_wilson@brown.edu>",
            "Renae Rodgers <rodge103@umn.edu>"]
@@ -29,7 +29,7 @@ mypy = "^1.0.1"
 pytest = "^8.3.4"
 pytest-cov = "^4.0.0"
 python-dotenv = "^1.0.0"
-fastapi = "^0.109.2"
+fastapi = "^0.115.12"
 uvicorn = {extras = ["standard"], version = "^0.34.1"}
 pytest-recording = "^0.12.2"
 vcrpy = "^4.2.1"
diff --git a/src/ipumspy/api/core.py b/src/ipumspy/api/core.py
index b6ca30f..721f177 100644
--- a/src/ipumspy/api/core.py
+++ b/src/ipumspy/api/core.py
@@ -592,7 +592,7 @@ def get_metadata_catalog(
 
         Args:
             collection: The name of the IPUMS collection to retrieve metadata for
-            metadata_type: Name of the type of metadata to retrieve for this collection
+            metadata_type: Name of the type of metadata to retrieve for this collection. Valid values for the NHGIS collection include 'datasets', 'data_tables', 'shapefiles', and 'time_series_tables'; valid values for the IHGIS collection include 'datasets', 'data_tables', and 'tabulation_geographies'.
             page_size: Number of items to return per page. Defaults to maximum page size, 2500.
 
         Yields:
diff --git a/src/ipumspy/api/extract.py b/src/ipumspy/api/extract.py
index 013da4a..9be95f2 100644
--- a/src/ipumspy/api/extract.py
+++ b/src/ipumspy/api/extract.py
@@ -57,6 +57,7 @@ class Variable(IpumsObject):
         case_selections: Case selection specifications
         attached_characteristics: Attach characteristics specifications
         data_quality_flags: Flag to include the variable's associated data quality flags if they exist
+        adjust_monetary_values: Flag to include the variable's associated inflation-adjusted equivalent, if possible
     """
 
     name: str
@@ -69,6 +70,8 @@ class Variable(IpumsObject):
     """Attach characteristics specifications"""
     data_quality_flags: Optional[bool] = False
     """Flag to include the variable's associated data quality flags if they exist"""
+    adjust_monetary_values: Optional[bool] = False
+    """Flag to include the variable's associated inflation-adjusted equivalent, if possible"""
 
     def __post_init__(self):
         self.name = self.name.upper()
@@ -82,6 +85,7 @@ def build(self):
         built_var["caseSelections"] = built_var.pop("case_selections")
         built_var["attachedCharacteristics"] = built_var.pop("attached_characteristics")
         built_var["dataQualityFlags"] = built_var.pop("data_quality_flags")
+        built_var["adjustMonetaryValues"] = built_var.pop("adjust_monetary_values")
         return built_var
 
 
@@ -144,7 +148,7 @@ def build(self):
 
 
 @dataclass
-class Dataset(IpumsObject):
+class NhgisDataset(IpumsObject):
     """
     IPUMS dataset object to include in an ``AggregateDataExtract`` object.
 
@@ -184,6 +188,38 @@ def build(self):
         return built_dataset
 
 
+@dataclass
+class IhgisDataset(IpumsObject):
+    """
+    IPUMS dataset object to include in an ``AggregateDataExtract`` object.
+
+    Args:
+        name: IPUMS dataset name
+        data_tables: IPUMS data tables to extract from this dataset
+        tabulation_geographies: Geographic level(s) at which to obtain data for this dataset
+    """
+
+    name: str
+    """IPUMS dataset name"""
+    data_tables: List[str]
+    """IPUMS data tables to extract from this dataset"""
+    tabulation_geographies: List[str]
+    """Geographic level(s) at which to obtain data for this dataset"""
+
+    def build(self):
+        """Format dataset information for API Extract submission"""
+        built_dataset = self.__dict__.copy()
+        # don't repeat the dataset name
+        built_dataset.pop("name")
+        # adhere to API schema camelCase convention
+        built_dataset["dataTables"] = built_dataset.pop("data_tables")
+        built_dataset["tabulationGeographies"] = built_dataset.pop(
+            "tabulation_geographies"
+        )
+
+        return built_dataset
+
+
 @dataclass
 class TimeSeriesTable(IpumsObject):
     """
@@ -269,10 +305,10 @@ def _unpack_tuv_dict(dct: dict) -> List[TimeUseVariable]:
     return tuvs
 
 
-def _unpack_dataset_dict(dct: dict) -> List[Dataset]:
+def _unpack_nhgis_dataset_dict(dct: dict) -> List[NhgisDataset]:
     datasets = []
     for dataset in dct.keys():
-        dataset_obj = Dataset(
+        dataset_obj = NhgisDataset(
             name=dataset,
             data_tables=dct[dataset]["dataTables"],
             geog_levels=dct[dataset]["geogLevels"],
@@ -285,6 +321,18 @@ def _unpack_dataset_dict(dct: dict) -> List[Dataset]:
     return datasets
 
 
+def _unpack_ihgis_dataset_dict(dct: dict) -> List[IhgisDataset]:
+    datasets = []
+    for dataset in dct.keys():
+        dataset_obj = IhgisDataset(
+            name=dataset,
+            data_tables=dct[dataset]["dataTables"],
+            tabulation_geographies=dct[dataset]["tabulationGeographies"],
+        )
+        datasets.append(dataset_obj)
+    return datasets
+
+
 def _unpack_tst_dict(dct: dict) -> List[TimeSeriesTable]:
     time_series_tables = []
     for time_series_table in dct.keys():
@@ -313,6 +361,7 @@ def _get_collection_type(collection: str) -> str:
         "nhis": "microdata",
         "meps": "microdata",
         "nhgis": "aggregate_data",
+        "ihgis": "aggregate_data",
     }
 
     return collection_types[collection]
@@ -408,10 +457,14 @@ def _snake_to_camel(self, kwarg_dict):
             camelized = "".join([k.capitalize() for k in key_list[1:]])
             # prepend the first part
             camel_key = f"{key_list[0]}{camelized}"
-            # add the camelCase key
-            kwarg_dict[camel_key] = kwarg_dict[key]
-            # pop the snake_case key
-            kwarg_dict.pop(key)
+
+            # Only replace the key if it has changed, otherwise it gets dropped
+            if camel_key != key:
+                # add the camelCase key
+                kwarg_dict[camel_key] = kwarg_dict[key]
+                # pop the snake_case key
+                kwarg_dict.pop(key)
+
         return kwarg_dict
 
     def _validate_list_args(self, list_arg, arg_obj):
@@ -422,7 +475,7 @@ def _validate_list_args(self, list_arg, arg_obj):
         # before diving into any duplicate validation, make sure the list argument the user provided
         # is only strings or only IPUMS objects. Raise a useful error and ask the user to fix themselves
         if not all(isinstance(i, str) for i in list_arg) and not all(
-            isinstance(i, IpumsObject) for i in list_arg
+            isinstance(i, arg_obj) for i in list_arg
         ):
             raise TypeError(
                 f"The items in {list_arg} must all be string type or {arg_obj} type."
@@ -436,8 +489,11 @@ def _validate_list_args(self, list_arg, arg_obj):
         elif isinstance(list_arg, dict) and arg_obj is TimeUseVariable:
             args = _unpack_tuv_dict(list_arg)
             return args
-        elif isinstance(list_arg, dict) and arg_obj is Dataset:
-            args = _unpack_dataset_dict(list_arg)
+        elif isinstance(list_arg, dict) and arg_obj is NhgisDataset:
+            args = _unpack_nhgis_dataset_dict(list_arg)
+            return args
+        elif isinstance(list_arg, dict) and arg_obj is IhgisDataset:
+            args = _unpack_ihgis_dataset_dict(list_arg)
             return args
         elif isinstance(list_arg, dict) and arg_obj is TimeSeriesTable:
             args = _unpack_tst_dict(list_arg)
@@ -688,12 +744,30 @@ def select_cases(
                 variable, "case_selections", {"detailed": values}
             )
 
+    def adjust_monetary_values(
+        self, variable: Union[Variable, str, List[Variable], List[str]]
+    ):
+        """
+        A method to update existing IPUMS Extract Variable objects to include that
+        variable's inflation-adjusted version in the extract if possible. This feature
+        is only applicable to variables representing dollar amounts.
+
+        Args:
+            variable: a Variable object or a string variable name
+
+        """
+        if isinstance(variable, list):
+            for v in variable:
+                self._update_variable_feature(v, "adjust_monetary_values", True)
+        else:
+            self._update_variable_feature(variable, "adjust_monetary_values", True)
+
 
 class AggregateDataExtract(BaseExtract, collection_type="aggregate_data"):
     def __init__(
         self,
         collection: str,
-        datasets: Optional[List[Dataset]] = [],
+        datasets: Optional[List[NhgisDataset] | List[IhgisDataset]] = [],
         time_series_tables: Optional[List[TimeSeriesTable]] = [],
         shapefiles: Optional[Union[List[str], List[Shapefile]]] = [],
         description: str = "",
@@ -707,16 +781,16 @@ def __init__(
         Class for defining an extract request for an IPUMS aggregate data collection.
 
         Args:
-            datasets: list of ``Dataset`` objects
-            time_series_tables: list of ``TimeSeriesTable`` objects
-            shapefiles: list of shapefile names
+            datasets: list of ``NhgisDataset`` objects (for NHGIS extracts) or ``IhgisDataset`` objects (for IHGIS extracts)
+            time_series_tables: list of ``TimeSeriesTable`` objects (for NHGIS extracts)
+            shapefiles: list of shapefile names (for NHGIS extracts)
             description: short description of your extract
-            data_format: desired format of the extract data file. One of ``"csv_no_header"``, ``"csv_header"``, or ``"fixed_width"``.
-            geographic_extents: Geographic extents to use for all ``datasets`` and ``time_series_tables`` in the extract definition (for instance, to
-                                to obtain data within a particular state).
+            data_format: desired format of the extract data file (for NHGIS extracts). One of ``"csv_no_header"``, ``"csv_header"``, or ``"fixed_width"``.
+            geographic_extents: Geographic extents to use for all ``datasets`` and ``time_series_tables`` in an NHGIS extract definition (for instance, to
+                                to obtain data within a particular state)
             tst_layout: desired data layout for all  ``time_series_tables`` in the extract definition.
-                        One of ``"time_by_column_layout"`` (default), ``"time_by_row_layout"``, or ``"time_by_file_layout"``.
-            breakdown_and_data_type_layout: desired layout of any ``datasets`` that have multiple data types or breakdown values. Either
+                        One of ``"time_by_column_layout"`` (default), ``"time_by_row_layout"``, or ``"time_by_file_layout"``
+            breakdown_and_data_type_layout: desired layout of any ``datasets`` that have multiple data types or breakdown values in an NHGIS extract definition. Either
                                             ``"single_file"`` (default) or ``"separate files"``
         """
 
@@ -726,26 +800,36 @@ def __init__(
         self.collection_type = self.collection_type
         """IPUMS collection type"""
 
-        self.datasets = self._validate_list_args(datasets, Dataset)
-        self.time_series_tables = self._validate_list_args(
-            time_series_tables, TimeSeriesTable
-        )
-        self.shapefiles = self._validate_list_args(shapefiles, Shapefile)
+        if collection == "nhgis":
+            self.datasets = self._validate_list_args(datasets, NhgisDataset)
+            self.data_format = data_format
+            self.geographic_extents = geographic_extents
+            self.breakdown_and_data_type_layout = breakdown_and_data_type_layout
+            self.tst_layout = tst_layout
 
-        if (
-            len(self.datasets) == 0
-            and len(self.time_series_tables) == 0
-            and len(self.shapefiles) == 0
-        ):
-            raise ValueError(
-                "At least one dataset, time series table, or shapefile must be specified."
+            self.time_series_tables = self._validate_list_args(
+                time_series_tables, TimeSeriesTable
             )
+            self.shapefiles = self._validate_list_args(shapefiles, Shapefile)
+
+            if (
+                len(self.datasets) == 0
+                and len(self.time_series_tables) == 0
+                and len(self.shapefiles) == 0
+            ):
+                raise ValueError(
+                    "At least one dataset, time series table, or shapefile must be specified."
+                )
+        elif collection == "ihgis":
+            self.datasets = self._validate_list_args(datasets, IhgisDataset)
+            self.data_format = None
+            self.geographic_extents = None
+            self.breakdown_and_data_type_layout = None
+            self.tst_layout = None
+            self.time_series_tables = None
+            self.shapefiles = None
 
         self.description = description
-        self.data_format = data_format
-        self.geographic_extents = geographic_extents
-        self.breakdown_and_data_type_layout = breakdown_and_data_type_layout
-        self.tst_layout = tst_layout
 
         self.api_version = (
             self.extract_api_version(kwargs)
@@ -767,7 +851,6 @@ def build(self) -> Dict[str, Any]:
 
         built = {
             "description": self.description,
-            "dataFormat": self.data_format,
             "collection": self.collection,
             "version": self.api_version,
             **self.kwargs,
@@ -777,10 +860,15 @@ def build(self) -> Dict[str, Any]:
             built["datasets"] = {
                 dataset.name: dataset.build() for dataset in self.datasets
             }
+
+        if self.data_format is not None:
+            built["dataFormat"] = self.data_format
+
+        if self.breakdown_and_data_type_layout is not None:
             built["breakdownAndDataTypeLayout"] = self.breakdown_and_data_type_layout
 
-            if self.geographic_extents is not None:
-                built["geographicExtents"] = self.geographic_extents
+        if self.geographic_extents is not None:
+            built["geographicExtents"] = self.geographic_extents
 
         if self.time_series_tables is not None:
             built["timeSeriesTables"] = {
diff --git a/src/ipumspy/api/metadata.py b/src/ipumspy/api/metadata.py
index a92ee24..b7963c3 100644
--- a/src/ipumspy/api/metadata.py
+++ b/src/ipumspy/api/metadata.py
@@ -43,19 +43,18 @@ def _validate_collection(self):
 
 
 @dataclass
-class DatasetMetadata(IpumsMetadata):
+class NhgisDatasetMetadata(IpumsMetadata):
     """
-    Class to request and store metadata for an IPUMS dataset
+    Class to request and store metadata for an IPUMS NHGIS dataset
 
     Args:
-        collection: name of an IPUMS data collection
-        name: Name of an IPUMS dataset included in the collection
+        name: Name of an IPUMS NHGIS dataset
     """
 
-    collection: str
-    """Name of an IPUMS data collection"""
     name: str
     """IPUMS dataset name"""
+    collection: str = "nhgis"
+    """Name of an IPUMS data collection"""
     nhgis_id: Optional[str] = field(default=None, init=False)
     """ID used in IPUMS files to reference the dataset"""
     group: Optional[str] = field(default=None, init=False)
@@ -99,6 +98,89 @@ def supported_collections(self):
         return ["nhgis"]
 
 
+@dataclass
+class IhgisDatasetMetadata(IpumsMetadata):
+    """
+    Class to request and store metadata for an IPUMS IHGIS dataset
+
+    Args:
+        name: Name of an IPUMS IHGIS dataset
+    """
+
+    name: str
+    """IPUMS IHGIS dataset name"""
+    collection: str = "ihgis"
+    """Name of an IPUMS data collection"""
+    description: Optional[str] = field(default=None, init=False)
+    """Title of the census"""
+    dataset_type: Optional[str] = field(default=None, init=False)
+    """Type of dataset (population, agricultural, or tabulated)"""
+    country: Optional[str] = field(default=None, init=False)
+    """Two-character abbreviation of the country"""
+    country_label: Optional[str] = field(default=None, init=False)
+    """Name of the country"""
+    year: Optional[str] = field(default=None, init=False)
+    """Year the census was conducted"""
+    statistical_agency: Optional[str] = field(default=None, init=False)
+    """Name of the statistical agency that conducted the census"""
+    universe: Optional[str] = field(default=None, init=False)
+    """Description of the population that was included in the enumeration"""
+    de_jure_de_facto: Optional[str] = field(default=None, init=False)
+    """
+    Whether the census counted people who reside in the country 
+        (including those who were absent on the census day) [de jure], or people who 
+        were present in the country on the census day (including visitors) [de facto].
+    """
+    enumeration_unit: Optional[str] = field(default=None, init=False)
+    """Types of entities (e.g., population, households, etc.) counted in the census"""
+    reference_period: Optional[str] = field(default=None, init=False)
+    """
+    Date of record; people who were residents of or present in the country 
+        as of this date were counted.
+    """
+    fieldwork_period: Optional[str] = field(default=None, init=False)
+    """Time period during which enumeration took place"""
+    fieldwork_type: Optional[str] = field(default=None, init=False)
+    """Methods used for enumeration, such as face-to-face interviews or online forms"""
+    enumeration_forms: Optional[str] = field(default=None, init=False)
+    """Type of enumeration forms used to collect information"""
+    coverage: Optional[str] = field(default=None, init=False)
+    """If available, an estimate of how complete the enumeration was"""
+    sample: Optional[str] = field(default=None, init=False)
+    """
+    If applicable, the proportion of the population included in the sample 
+        on which the data tables are based
+    """
+    dwelling_definition: Optional[str] = field(default=None, init=False)
+    """Definition used by the census of what constitutes a distinct dwelling unit"""
+    household_definition: Optional[str] = field(default=None, init=False)
+    """Definition used by the census of how people are grouped into households"""
+    group_quarters_definition: Optional[str] = field(default=None, init=False)
+    """Definition used by the census of what constitutes group quarters"""
+    sequence: Optional[str] = field(default=None, init=False)
+    """Order in which the dataset will appear"""
+    data_table_count: Optional[str] = field(default=None, init=False)
+    """Number of data tables included in the dataset"""
+    data_tables: Optional[List[Dict]] = field(default=None, init=False)
+    """
+    Dictionary containing names, codes, and descriptions for the data tables 
+        available for the dataset
+    """
+    tabulation_geographies: Optional[List[Dict]] = field(default=None, init=False)
+    """
+    Dictionary containing names, codes, and descriptions for the tabulation 
+        geographies available for the dataset
+    """
+
+    def __post_init__(self):
+        self._path = f"metadata/datasets/{self.name}"
+        self._validate_collection()
+
+    @property
+    def supported_collections(self):
+        return ["ihgis"]
+
+
 @dataclass
 class TimeSeriesTableMetadata(IpumsMetadata):
     """
@@ -142,22 +224,21 @@ def supported_collections(self):
 
 
 @dataclass
-class DataTableMetadata(IpumsMetadata):
+class NhgisDataTableMetadata(IpumsMetadata):
     """
-    Class to request and store metadata for an IPUMS data table
+    Class to request and store metadata for an IPUMS NHGIS data table
 
     Args:
-        collection: IPUMS collection associated with this data table
-        name: Name of the data table for which to retrieve metadata
-        dataset_name: Name of the dataset containing this data table
+        name: Name of the NHGIS data table for which to retrieve metadata
+        dataset_name: Name of the NHGIS dataset containing this data table
     """
 
-    collection: str
-    """Name of an IPUMS data collection"""
     name: str
     """IPUMS data table name"""
     dataset_name: str
     """Name of the dataset to which this data table belongs"""
+    collection: str = "nhgis"
+    """Name of an IPUMS data collection"""
     description: Optional[str] = field(default=None, init=False)
     """Description of the data table"""
     universe: Optional[str] = field(default=None, init=False)
@@ -173,11 +254,51 @@ class DataTableMetadata(IpumsMetadata):
     """Dictionary containing variable descriptions and codes for the variables included in the data table"""
 
     def __post_init__(self):
-        self._path = self._path = (
-            f"metadata/datasets/{self.dataset_name}/data_tables/{self.name}"
-        )
+        self._path = f"metadata/datasets/{self.dataset_name}/data_tables/{self.name}"
         self._validate_collection()
 
     @property
     def supported_collections(self):
         return ["nhgis"]
+
+
+@dataclass
+class IhgisDataTableMetadata(IpumsMetadata):
+    """
+    Class to request and store metadata for an IPUMS IHGIS data table
+
+    Args:
+        name: Name of an IPUMS IHGIS data table
+    """
+
+    name: str
+    """IPUMS data table name"""
+    dataset_name: Optional[str] = field(default=None, init=False)
+    """Name of the dataset to which this data table belongs"""
+    collection: str = "ihgis"
+    """Name of an IPUMS data collection"""
+    label: Optional[str] = field(default=None, init=False)
+    """Title of the data table"""
+    universe: Optional[str] = field(default=None, init=False)
+    """
+    Statistical population measured by this data table, including 
+        any restrictions on who or what was included
+    """
+    table_num: Optional[str] = field(default=None, init=False)
+    """Number designating the table in the source publication"""
+    sequence: Optional[str] = field(default=None, init=False)
+    """Order in which the data table will appear in the metadata API and extracts"""
+    tabulation_geographies: Optional[str] = field(default=None, init=False)
+    """Tabulation geographies for which this table is available"""
+    footnotes: Optional[str] = field(default=None, init=False)
+    """Explanatory footnotes associated with the table"""
+    variables: Optional[str] = field(default=None, init=False)
+    """Dictionary containing variable descriptions and codes for the variables included in the data table"""
+
+    def __post_init__(self):
+        self._path = f"metadata/data_tables/{self.name}"
+        self._validate_collection()
+
+    @property
+    def supported_collections(self):
+        return ["ihgis"]
diff --git a/tests/cassettes/test_api/test_adjust_monetary_values_errors.yaml b/tests/cassettes/test_api/test_adjust_monetary_values_errors.yaml
new file mode 100644
index 0000000..9a37430
--- /dev/null
+++ b/tests/cassettes/test_api/test_adjust_monetary_values_errors.yaml
@@ -0,0 +1,133 @@
+interactions:
+- request:
+    body: '{"description": "My IPUMS CPS extract", "dataFormat": "fixed_width", "dataStructure":
+      {"rectangular": {"on": "P"}}, "samples": {"cps2012_03s": {}}, "variables": {"AGE":
+      {"preselected": false, "caseSelections": {}, "attachedCharacteristics": [],
+      "dataQualityFlags": false, "adjustMonetaryValues": false}, "SEX": {"preselected":
+      false, "caseSelections": {}, "attachedCharacteristics": [], "dataQualityFlags":
+      false, "adjustMonetaryValues": true}, "HOURWAGE": {"preselected": false, "caseSelections":
+      {}, "attachedCharacteristics": [], "dataQualityFlags": false, "adjustMonetaryValues":
+      false}}, "collection": "cps", "version": 2}'
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '627'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - python-ipumspy:0.6.2.github.com/ipums/ipumspy
+    method: POST
+    uri: https://api.ipums.org/extracts?collection=cps&version=2
+  response:
+    body:
+      string: '{"type":"SemanticValidationError","status":{"code":400,"name":"Bad
+        Request"},"detail":["Monetary value adjustment is not supported for SEX."]}'
+    headers:
+      Cache-Control:
+      - no-cache
+      Content-Length:
+      - '142'
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Wed, 28 May 2025 15:46:19 GMT
+      Referrer-Policy:
+      - strict-origin-when-cross-origin
+      Server:
+      - nginx/1.22.1
+      Vary:
+      - Origin
+      - Accept
+      X-Content-Type-Options:
+      - nosniff
+      X-Frame-Options:
+      - SAMEORIGIN
+      X-Permitted-Cross-Domain-Policies:
+      - none
+      X-Ratelimit-Limit:
+      - '-1'
+      X-Ratelimit-Remaining:
+      - '0'
+      X-Ratelimit-Reset:
+      - '0'
+      X-Request-Id:
+      - 7a274944-f227-408a-9570-a6d9e2df9c9c
+      X-Runtime:
+      - '0.691613'
+      X-Xss-Protection:
+      - '0'
+    status:
+      code: 400
+      message: Bad Request
+- request:
+    body: '{"description": "My IPUMS ATUS extract", "dataFormat": "fixed_width", "dataStructure":
+      {"rectangular": {"on": "P"}}, "samples": {"at2012": {}}, "variables": {"AGE":
+      {"preselected": false, "caseSelections": {}, "attachedCharacteristics": [],
+      "dataQualityFlags": false, "adjustMonetaryValues": false}, "SEX": {"preselected":
+      false, "caseSelections": {}, "attachedCharacteristics": [], "dataQualityFlags":
+      false, "adjustMonetaryValues": false}, "EARNWEEK": {"preselected": false, "caseSelections":
+      {}, "attachedCharacteristics": [], "dataQualityFlags": false, "adjustMonetaryValues":
+      true}}, "collection": "atus", "version": 2}'
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '624'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - python-ipumspy:0.6.2.github.com/ipums/ipumspy
+    method: POST
+    uri: https://api.ipums.org/extracts?collection=atus&version=2
+  response:
+    body:
+      string: '{"type":"SemanticValidationError","status":{"code":400,"name":"Bad
+        Request"},"detail":["Monetary value adjustment is not supported for IPUMS
+        ATUS"]}'
+    headers:
+      Cache-Control:
+      - no-cache
+      Content-Length:
+      - '148'
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Wed, 28 May 2025 15:46:19 GMT
+      Referrer-Policy:
+      - strict-origin-when-cross-origin
+      Server:
+      - nginx/1.22.1
+      Vary:
+      - Origin
+      - Accept
+      X-Content-Type-Options:
+      - nosniff
+      X-Frame-Options:
+      - SAMEORIGIN
+      X-Permitted-Cross-Domain-Policies:
+      - none
+      X-Ratelimit-Limit:
+      - '-1'
+      X-Ratelimit-Remaining:
+      - '0'
+      X-Ratelimit-Reset:
+      - '0'
+      X-Request-Id:
+      - 53660b57-cfcd-46e1-9699-6ad7d2dd4203
+      X-Runtime:
+      - '0.517223'
+      X-Xss-Protection:
+      - '0'
+    status:
+      code: 400
+      message: Bad Request
+version: 1
diff --git a/tests/cassettes/test_metadata/test_get_metadata.yaml b/tests/cassettes/test_metadata/test_get_nhgis_metadata.yaml
similarity index 76%
rename from tests/cassettes/test_metadata/test_get_metadata.yaml
rename to tests/cassettes/test_metadata/test_get_nhgis_metadata.yaml
index 4087bb2..4f3308f 100644
--- a/tests/cassettes/test_metadata/test_get_metadata.yaml
+++ b/tests/cassettes/test_metadata/test_get_nhgis_metadata.yaml
@@ -122,24 +122,24 @@ interactions:
         of Value","universe":"Specified owner-occupied housing units","nhgisCode":"ETT","sequence":97,"datasetName":"1990_STF1","nVariables":3},{"name":"NH53","description":"Imputation
         of Price Asked","universe":"Specified Vacant-for-Sale Only Housing Units","nhgisCode":"ETU","sequence":98,"datasetName":"1990_STF1","nVariables":3},{"name":"NH54","description":"Imputation
         of Contract Rent","universe":"Specified renter-occupied housing units","nhgisCode":"ETV","sequence":99,"datasetName":"1990_STF1","nVariables":4},{"name":"NH55","description":"Imputation
-        of Meals Included in Rent","universe":"Specified renter-occupied housing units","nhgisCode":"ETW","sequence":100,"datasetName":"1990_STF1","nVariables":4}],"geogLevels":[{"name":"nation","description":"Nation","hasGeogExtentSelection":false,"sequence":1},{"name":"region","description":"Region","hasGeogExtentSelection":false,"sequence":2},{"name":"division","description":"Division","hasGeogExtentSelection":false,"sequence":3},{"name":"state","description":"State","hasGeogExtentSelection":false,"sequence":4},{"name":"state_260","description":"American
-        Indian Area/Alaska Native Area/Hawaiian Home Land--State","hasGeogExtentSelection":false,"sequence":5},{"name":"state_262","description":"American
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+        Indian Area/Alaska Native Area (Reservation or Statistical Entity Only)--State","hasGeogExtentSelection":true,"sequence":7},{"name":"state_264","description":"American
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         Statistical Area/Consolidated Metropolitan Statistical Area--Primary Metropolitan
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+        Indian Area/Alaska Native Area/Hawaiian Home Land--State--County","hasGeogExtentSelection":true,"sequence":53},{"name":"county_272","description":"American
+        Indian Area/Alaska Native Area (Reservation or Statistical Entity Only)--State--County","hasGeogExtentSelection":true,"sequence":54},{"name":"county_274","description":"American
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-        District (1987-1993, 100th-102nd Congress)","hasGeogExtentSelection":false,"sequence":222},{"name":"anrc","description":"Alaska
+        Statistical Area--State--Central City","hasGeogExtentSelection":true,"sequence":194},{"name":"place_460","description":"Urban
+        Area--State--Central Place","hasGeogExtentSelection":true,"sequence":197},{"name":"place_450","description":"Urban
+        Area--State--County--County Subdivision--Place/Remainder","hasGeogExtentSelection":true,"sequence":198},{"name":"c_city","description":"State--Consolidated
+        City","hasGeogExtentSelection":true,"sequence":201},{"name":"c_city_541_103","description":"State--Congressional
+        District (1993-1995, 103rd Congress)--Consolidated City [10000 or more persons]","hasGeogExtentSelection":true,"sequence":208},{"name":"cd103rd","description":"State--Congressional
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+        District (1993-1995, 103rd Congress)--Alaska Native Regional Corporation","hasGeogExtentSelection":true,"sequence":265},{"name":"aianhh","description":"American
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-        Trust Land Only)/Hawaiian Home Land","hasGeogExtentSelection":false,"sequence":302},{"name":"msa_cmsa","description":"Metropolitan
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         Statistical Area/Consolidated Metropolitan Statistical Area","hasGeogExtentSelection":false,"sequence":346},{"name":"pmsa_385","description":"Metropolitan
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+      Connection:
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+      User-Agent:
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+    method: GET
+    uri: https://api.ipums.org/metadata/time_series_tables/CW3?collection=nhgis&pageSize=2500&version=2
+  response:
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+        Island"},{"name":"450","description":"South Carolina"},{"name":"460","description":"South
+        Dakota"},{"name":"470","description":"Tennessee"},{"name":"480","description":"Texas"},{"name":"490","description":"Utah"},{"name":"500","description":"Vermont"},{"name":"510","description":"Virginia"},{"name":"530","description":"Washington"},{"name":"540","description":"West
+        Virginia"},{"name":"550","description":"Wisconsin"},{"name":"560","description":"Wyoming"}]}'
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diff --git a/tests/fixtures/nhgis_extract_v2.pkl b/tests/fixtures/nhgis_extract_v2.pkl
index 2f8e5fd..3c41029 100644
Binary files a/tests/fixtures/nhgis_extract_v2.pkl and b/tests/fixtures/nhgis_extract_v2.pkl differ
diff --git a/tests/test_api.py b/tests/test_api.py
index d08d5ab..b39f1d7 100644
--- a/tests/test_api.py
+++ b/tests/test_api.py
@@ -24,7 +24,8 @@
     Variable,
     Sample,
     TimeUseVariable,
-    Dataset,
+    NhgisDataset,
+    IhgisDataset,
     TimeSeriesTable,
     Shapefile,
 )
@@ -74,7 +75,7 @@ def simple_nhgis_extract() -> AggregateDataExtract:
     extract = AggregateDataExtract(
         "nhgis",
         description="Simple extract for ipumspy unit testing",
-        datasets=[Dataset("1990_STF1", ["NP1"], ["state"])],
+        datasets=[NhgisDataset("1990_STF1", ["NP1"], ["state"])],
     )
 
     return extract
@@ -86,8 +87,8 @@ def complex_nhgis_extract() -> AggregateDataExtract:
         "nhgis",
         description="Complex extract for ipumspy unit testing",
         datasets=[
-            Dataset("2010_SF1a", ["P1", "P2"], ["block"]),
-            Dataset(
+            NhgisDataset("2010_SF1a", ["P1", "P2"], ["block"]),
+            NhgisDataset(
                 "2010_SF2a",
                 ["PCT1"],
                 ["state"],
@@ -105,6 +106,23 @@ def complex_nhgis_extract() -> AggregateDataExtract:
     return extract
 
 
+@pytest.fixture()
+def ihgis_extract() -> AggregateDataExtract:
+    extract = AggregateDataExtract(
+        "ihgis",
+        description="IHGIS extract for ipumspy unit testing",
+        datasets=[
+            IhgisDataset(
+                "KZ2009pop",
+                data_tables=["KZ2009pop.AAA", "KZ2009pop.AAB"],
+                tabulation_geographies=["KZ2009pop.g0", "KZ2009pop.g1"],
+            )
+        ],
+    )
+
+    return extract
+
+
 def test_usa_build_extract():
     """
     Confirm that test extract formatted correctly
@@ -124,12 +142,14 @@ def test_usa_build_extract():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS USA extract",
@@ -158,12 +178,14 @@ def test_usa_attach_characteristics():
                 "caseSelections": {},
                 "attachedCharacteristics": ["father"],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS USA extract",
@@ -180,7 +202,7 @@ def test_usa_attach_characteristics():
 
 def test_usa_add_data_quality_flags():
     """
-    Confirm that attach_characteristics updates extract definition correctly
+    Confirm that add_data_quality_flags updates extract definition correctly
     """
     extract = MicrodataExtract(
         "usa",
@@ -197,18 +219,21 @@ def test_usa_add_data_quality_flags():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": True,
+                "adjustMonetaryValues": False,
             },
             "RACE": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS USA extract",
@@ -234,18 +259,21 @@ def test_usa_add_data_quality_flags():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": True,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "RACE": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": True,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS USA extract",
@@ -275,12 +303,14 @@ def test_usa_select_cases():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "RACE": {
                 "preselected": False,
                 "caseSelections": {"general": ["1"]},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS USA extract",
@@ -299,12 +329,14 @@ def test_usa_select_cases():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "RACE": {
                 "preselected": False,
                 "caseSelections": {"detailed": ["100"]},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS USA extract",
@@ -389,7 +421,7 @@ def test_nhgis_feature_errors(live_api_client: IpumsApiClient):
     """
     extract = AggregateDataExtract(
         "nhgis",
-        datasets=[Dataset("a", "b", "c", "d")],
+        datasets=[NhgisDataset("a", "b", "c", "d")],
         time_series_tables=[TimeSeriesTable("a", "b")],
     )
 
@@ -433,12 +465,14 @@ def test_cps_build_extract():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "description": "My IPUMS CPS extract",
@@ -468,12 +502,14 @@ def test_ipumsi_build_extract():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "collection": "ipumsi",
@@ -499,12 +535,14 @@ def test_atus_build_extract():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "timeUseVariables": {"BLS_PCARE": {}},
@@ -530,12 +568,14 @@ def test_atus_build_extract():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "timeUseVariables": {"BLS_PCARE": {}},
@@ -566,12 +606,14 @@ def test_atus_build_extract():
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "timeUseVariables": {
@@ -664,6 +706,20 @@ def test_nhgis_build_extract(
     }
 
 
+def test_ihgis_build_extract(ihgis_extract: AggregateDataExtract):
+    assert ihgis_extract.build() == {
+        "description": "IHGIS extract for ipumspy unit testing",
+        "collection": "ihgis",
+        "version": None,
+        "datasets": {
+            "KZ2009pop": {
+                "dataTables": ["KZ2009pop.AAA", "KZ2009pop.AAB"],
+                "tabulationGeographies": ["KZ2009pop.g0", "KZ2009pop.g1"],
+            },
+        },
+    }
+
+
 @pytest.mark.vcr
 def test_rect_on_nonP_extract(live_api_client: IpumsApiClient):
     bad_hs_ext = MicrodataExtract(
@@ -832,6 +888,7 @@ def test_extract_from_dict(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="SEX",
@@ -839,6 +896,7 @@ def test_extract_from_dict(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="RACE",
@@ -846,6 +904,7 @@ def test_extract_from_dict(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
         ]
         # data structure not currently an extract attribute...
@@ -866,6 +925,7 @@ def test_extract_from_dict(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=["mother"],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="SEX",
@@ -873,6 +933,7 @@ def test_extract_from_dict(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="RACE",
@@ -880,6 +941,7 @@ def test_extract_from_dict(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
         ]
         # data structure not currently an extract attribute...
@@ -909,10 +971,12 @@ def test_nhgis_extract_from_dict(fixtures_path: Path):
         for item in extract:
             assert item.collection == "nhgis"
             assert item.datasets == [
-                Dataset(
+                NhgisDataset(
                     name="1990_STF1", data_tables=["NP1", "NP2"], geog_levels=["county"]
                 ),
-                Dataset(name="2010_SF1a", data_tables=["P1"], geog_levels=["state"]),
+                NhgisDataset(
+                    name="2010_SF1a", data_tables=["P1"], geog_levels=["state"]
+                ),
             ]
             assert item.time_series_tables == [
                 TimeSeriesTable(name="CW3", geog_levels=["state"], years=["1990"])
@@ -1140,6 +1204,7 @@ def test_define_extract_from_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="SEX",
@@ -1147,6 +1212,7 @@ def test_define_extract_from_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="RACE",
@@ -1154,6 +1220,7 @@ def test_define_extract_from_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
         ]
         assert item.api_version == 2
@@ -1171,6 +1238,7 @@ def test_define_extract_from_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=["mother"],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="SEX",
@@ -1178,6 +1246,7 @@ def test_define_extract_from_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="RACE",
@@ -1185,6 +1254,7 @@ def test_define_extract_from_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
         ]
         assert item.api_version == 2
@@ -1216,6 +1286,7 @@ def test_extract_from_api_response_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="AGE",
@@ -1223,6 +1294,7 @@ def test_extract_from_api_response_json(fixtures_path: Path):
                 case_selections={"general": [1, 2, 3]},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="SEX",
@@ -1230,6 +1302,7 @@ def test_extract_from_api_response_json(fixtures_path: Path):
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=True,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="RACE",
@@ -1311,6 +1384,7 @@ def test_validate_list_args():
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="SEX",
@@ -1318,6 +1392,7 @@ def test_validate_list_args():
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
             Variable(
                 name="RACE",
@@ -1325,6 +1400,7 @@ def test_validate_list_args():
                 case_selections={},
                 attached_characteristics=[],
                 data_quality_flags=False,
+                adjust_monetary_values=False,
             ),
         ]
     )
@@ -1395,7 +1471,7 @@ def test_validate_list_args():
         )
     assert (
         exc_info.value.args[0]
-        == "The items in [Variable(name='AGE', preselected=False, case_selections={}, attached_characteristics=[], data_quality_flags=False), 'SEX'] must all be string type or <class 'ipumspy.api.extract.Variable'> type."
+        == "The items in [Variable(name='AGE', preselected=False, case_selections={}, attached_characteristics=[], data_quality_flags=False, adjust_monetary_values=False), 'SEX'] must all be string type or <class 'ipumspy.api.extract.Variable'> type."
     )
 
 
@@ -1417,66 +1493,77 @@ def test_get_extract_by_id(live_api_client: IpumsApiClient):
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SERIAL": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "MONTH": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "HWTFINL": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "CPSID": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "PERNUM": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "WTFINL": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "CPSIDP": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "AGE": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "RACE": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "collection": "cps",
@@ -1497,54 +1584,63 @@ def test_get_extract_by_id(live_api_client: IpumsApiClient):
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "YEAR": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SAMPLE": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SERIAL": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "HHWT": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "PERNUM": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "PERWT": {
                 "preselected": True,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "AGE": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
             "SEX": {
                 "preselected": False,
                 "caseSelections": {},
                 "attachedCharacteristics": [],
                 "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
             },
         },
         "collection": "ipumsi",
@@ -1724,3 +1820,76 @@ def test_get_pages(live_api_client: IpumsApiClient):
         live_api_client._get_pages(collection="usa", endpoint="extracts", page_size=5)
     )
     assert len(page1["data"]) == 5
+
+
+def test_cps_adjust_monetary_values():
+    """
+    Confirm that adjust monetary values updates are happening correctly
+    """
+    extract = MicrodataExtract(
+        "cps",
+        ["cps2012_03s"],
+        ["AGE", "SEX", "HOURWAGE"],
+    )
+    extract.adjust_monetary_values("HOURWAGE")
+    assert extract.build() == {
+        "dataStructure": {"rectangular": {"on": "P"}},
+        "samples": {"cps2012_03s": {}},
+        "variables": {
+            "AGE": {
+                "preselected": False,
+                "caseSelections": {},
+                "attachedCharacteristics": [],
+                "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
+            },
+            "SEX": {
+                "preselected": False,
+                "caseSelections": {},
+                "attachedCharacteristics": [],
+                "dataQualityFlags": False,
+                "adjustMonetaryValues": False,
+            },
+            "HOURWAGE": {
+                "preselected": False,
+                "caseSelections": {},
+                "attachedCharacteristics": [],
+                "dataQualityFlags": False,
+                "adjustMonetaryValues": True,
+            },
+        },
+        "description": "My IPUMS CPS extract",
+        "dataFormat": "fixed_width",
+        "collection": "cps",
+        "version": None,
+    }
+
+
+@pytest.mark.vcr
+def test_adjust_monetary_values_errors(live_api_client: IpumsApiClient):
+    """Confirm correct errors raised by trying to adjust a non-monetary variable"""
+    extract = MicrodataExtract(
+        "cps",
+        ["cps2012_03s"],
+        ["AGE", "SEX", "HOURWAGE"],
+    )
+    extract.adjust_monetary_values("SEX")
+    with pytest.raises(BadIpumsApiRequest) as exc_info:
+        live_api_client.submit_extract(extract)
+    assert (
+        exc_info.value.args[0] == "Monetary value adjustment is not supported for SEX."
+    )
+
+    extract = MicrodataExtract(
+        "atus",
+        ["at2012"],
+        ["AGE", "SEX", "EARNWEEK"],
+    )
+
+    extract.adjust_monetary_values("EARNWEEK")
+    with pytest.raises(BadIpumsApiRequest) as exc_info:
+        live_api_client.submit_extract(extract)
+    assert (
+        exc_info.value.args[0]
+        == "Monetary value adjustment is not supported for IPUMS ATUS"
+    )
diff --git a/tests/test_metadata.py b/tests/test_metadata.py
index d4bd36e..6feeb24 100644
--- a/tests/test_metadata.py
+++ b/tests/test_metadata.py
@@ -4,8 +4,10 @@
 from ipumspy.api import IpumsApiClient
 
 from ipumspy.api.metadata import (
-    DatasetMetadata,
-    DataTableMetadata,
+    NhgisDatasetMetadata,
+    NhgisDataTableMetadata,
+    IhgisDatasetMetadata,
+    IhgisDataTableMetadata,
     TimeSeriesTableMetadata,
 )
 
@@ -49,29 +51,55 @@ def test_get_metadata_catalog(live_api_client: IpumsApiClient):
 
 
 @pytest.mark.vcr
-def test_get_metadata(live_api_client: IpumsApiClient):
-    ds = DatasetMetadata("nhgis", "1990_STF1")
-    dt = DataTableMetadata("nhgis", "B01001", "2017_2021_ACS5a")
+def test_get_nhgis_metadata(live_api_client: IpumsApiClient):
+    ds = NhgisDatasetMetadata("1990_STF1")
+    dt = NhgisDataTableMetadata("B01001", "2017_2021_ACS5a")
+    tt = TimeSeriesTableMetadata("nhgis", "CW3")
 
     ds = live_api_client.get_metadata(ds)
     dt = live_api_client.get_metadata(dt)
+    tt = live_api_client.get_metadata(tt)
 
-    assert isinstance(ds, DatasetMetadata)
-    assert isinstance(dt, DataTableMetadata)
+    assert isinstance(ds, NhgisDatasetMetadata)
+    assert isinstance(dt, NhgisDataTableMetadata)
+    assert isinstance(tt, TimeSeriesTableMetadata)
 
     assert ds.description == "STF 1 - 100% Data"
     assert dt.description == "Sex by Age"
+    assert tt.description == "Persons by Age [22]"
 
     assert len(ds.data_tables) == 100
     assert len(dt.variables) == 49
+    assert len(tt.time_series) == 22
+
+
+# TODO: Enable test when IHGIS released to live. Currently only on demo
+"""
+@pytest.mark.vcr
+def test_get_ihgis_metadata(live_api_client: IpumsApiClient):
+    ds = IhgisDatasetMetadata("KZ2009pop")
+    dt = IhgisDataTableMetadata("KZ2009pop.AAA")
+
+    ds = live_api_client.get_metadata(ds)
+    dt = live_api_client.get_metadata(dt)
+
+    assert isinstance(ds, IhgisDatasetMetadata)
+    assert isinstance(dt, IhgisDataTableMetadata)
+
+    assert ds.description == "Results of the 2009 National Population Census of the Republic of Kazakhstan"
+    assert dt.label == "Urban and rural population"
+
+    assert len(ds.data_tables) == 6
+    assert len(dt.variables) == 9
+"""
 
 
 def test_collection_validity():
     with pytest.raises(ValueError) as exc_info:
-        ds = DatasetMetadata("usa", "1990_STF1")
+        ds = TimeSeriesTableMetadata("usa", "CW3")
     assert (
         exc_info.value.args[0]
-        == "DatasetMetadata is not a valid metadata type for the usa collection."
+        == "TimeSeriesTableMetadata is not a valid metadata type for the usa collection."
     )
 
 
diff --git a/tests/test_readers.py b/tests/test_readers.py
index 289ade3..153fd5b 100644
--- a/tests/test_readers.py
+++ b/tests/test_readers.py
@@ -896,6 +896,7 @@ def test_read_extract_description(fixtures_path: Path):
         "caseSelections": {"general": [1, 2, 3]},
         "attachedCharacteristics": [],
         "dataQualityFlags": False,
+        "adjustMonetaryValues": False,
     }
 
     # Check that something that is neither YAML nor JSON yields a ValueError