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  <titleInfo>
    <title>Using stata for principles of econometrics</title>
  </titleInfo>
  <name type="personal">
    <namePart>Adkins, Lee C.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  </name>
  <name type="personal">
    <namePart>Hill, R. Carter</namePart>
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  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">nju</placeTerm>
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    <place>
      <placeTerm type="text">New York</placeTerm>
    </place>
    <publisher>Wiley</publisher>
    <dateIssued>2011</dateIssued>
    <edition>4th ed.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>xii, 611 p. : ill. ; 28 cm.</extent>
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  <abstract>Using Stata for Principles of Econometrics is a cutting edge text which incorporates the capabilities of Stata software to practically apply the principles of econometrics. Readers will learn how to apply basic econometric tools and the Stata software to estimation, inference and forecasting in the context of real world economic problems. In order to make concepts more accessible, it also offers lucid descriptions of techniques as well as appropriate applications to today's situations. Along the way, readers will find introductionsto simple economic models and questions to enhance critical thinking</abstract>
  <abstract>Econometrics</abstract>
  <tableOfContents>Introducing Stata -- Simple linear regression -- Interval estimation and hypothesis testing -- Prediction, goodness of fit and modeling issues -- Multiple linear regression -- Further inference in the multiple regression model -- Using indicator variables -- Heteroskedasticity -- Regression with time-series data : stationary variables -- Random regressors and moment based estimation -- Simultaneous equations models -- Regression with time- series data : nonstationary variables -- Vector error correction and vector autoregressive models -- Time- varying volatility and ARCH models -- Panel data models -- Qualitative and limited dependent variable models</tableOfContents>
  <targetAudience authority="marctarget">general</targetAudience>
  <note type="statement of responsibility">Lee C. Adkins, R. Carter Hill</note>
  <note>Includes index</note>
  <identifier type="isbn">9781118032084</identifier>
  <identifier type="isbn">111803208X</identifier>
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