The median earnings of Mountain Home Micro Area (AR) was $21,753 in 2013.

Earnings and Gender

Earnings and Education

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

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Jobs and Earnings Datasets Involving Mountain Home Micro Area (AR)

  • API

    State Profiles: FY 2014 Public Libraries Survey (Data)

    data.imls.gov | Last Updated 2016-12-07T00:10:49.000Z

    Pull up a state's profile to find state-level totals on key data such as numbers of libraries and librarians, revenue and expenditures, and collection sizes.<br><br>These data include imputed values for libraries that did not submit information in the FY 2014 data collection. Imputation is a procedure for estimating a value for a specific data item where the response is missing. <br><br>Download PLS data files to see imputation flag variables or learn more on the imputation methods used in FY 2014 at https://www.imls.gov/research-evaluation/data-collection/public-libraries-survey/explore-pls-data/pls-data

  • API

    Structural Fiscal Balances Database for Latin America and the Caribbean

    mydata.iadb.org | Last Updated 2017-06-30T18:16:07.000Z

    The database allows estimating structural fiscal balances for 20 countries in the region under different assumptions regarding the output gap and commodity structural prices. It is a unique database of its kind since: 1) It takes into consideration the distinct responsiveness of different types of revenues to changes in the output gap: In order to adjust for the impact of the business cycle on revenues, we calculate individual elasticities for each source of revenue (i.e. direct taxes, indirect taxes, revenues from non-renewable resources, etc.). Since the different types of revenues in the region have different sensitivities to changes in the output gap, this disaggregated approach allows for a more fine-tuned adjustment. 2) It includes estimations of SFBs based on output gaps’ projections available in “real time”. In addition to giving estimations of the actual SFBs, we provide with estimations of the SFBs that would have resulted should the projections on output gaps available to policymakers at the time of designing fiscal policy (data in “real time”) have been correct. This is in contrast to much of the existing work on structural fiscal balances that makes only an “ex post” analysis using actual and revised information on the output gaps. 3) It allows assessing the response of fiscal policy to the business cycle. We provide with measures of the fiscal impulse, assessing not only the actual but also the intentional fiscal stance, as well as the degree of procyclicality of fiscal policy.<br><br><b>Click here to access the data: https://mydata.iadb.org/idb/dataset/3itg-avtz</b></br></br>

  • API

    Public Management Evaluation Tool

    mydata.iadb.org | Last Updated 2017-07-05T20:28:43.000Z

    The Public Management Evaluation Tool (PET) evaluates five “pillars” of the public policies' management cycle that are considered important for the implementation of Management for Development Results (MfDR): (i) results-based planning, (ii) results-based budgeting, (iii) public financial management (including auditing and procurement), (iv) program and project management (including the public investment system), and (v) monitoring and evaluation of public management. These pillars are broken down into components that track the maturity of institutional systems. The components are in turn composed of indicators and minimum requirements that these systems must have in an MfDR environment. All of these measures (minimum requirements, indicators, components, and pillars) are scored on a scale from 0 to 5, where a 5 indicates an ideal institutional situation. <br><br><b>Click here to access the data: https://mydata.iadb.org/idb/dataset/c89t-dh9r</b></br></br>