Introductory Econometrics - Unit 1
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Questions and Answers

What type of variable is 'Wage' classified as?

  • Nominal
  • Ordinal
  • Binary
  • Cardinal (correct)

    • Which variable type is 'Highest grade attended' categorized under?

  • Ordinal (correct)
  • Nominal
  • Cardinal
  • Binary

    • How is the variable 'Sex' best classified?

  • Ordinal
  • Continuous
  • Cardinal
  • Nominal (correct)

    • Which of the following variables is considered nominal?

    <p>Race</p> Signup and view all the answers

    What does the variable 'No. of own kids' represent in terms of variable type?

    <p>Cardinal</p> Signup and view all the answers

    What is the maximum wage recorded in the dataset?

    <p>50000</p> Signup and view all the answers

    How many individuals in the dataset are identified as female?

    <p>7</p> Signup and view all the answers

    Which individual has the highest age in the dataset?

    <p>75</p> Signup and view all the answers

    What is the most common level of education indicated in the dataset?

    <p>1</p> Signup and view all the answers

    How many people in the dataset are married?

    <p>9</p> Signup and view all the answers

    What is the age of the youngest individual in the dataset?

    <p>1</p> Signup and view all the answers

    Which of the following individuals works the most hours?

    <p>Individual 17</p> Signup and view all the answers

    How many children does the individual with the highest wage have?

    <p>3</p> Signup and view all the answers

    What is the null hypothesis for testing if the expected value of BMI is significantly different from 25?

    <p>H0: E[BMI] = 25</p> Signup and view all the answers

    In a two-sided t-test with a significance level of 5%, what are the critical values?

    <p>-1.96 and 1.96</p> Signup and view all the answers

    Why are one-sided t-tests reasonable in certain economic considerations?

    <p>They focus on extreme deviations from the null hypothesis.</p> Signup and view all the answers

    What is the t-value computed for the BMI based on the given expected value and standard deviation in the example?

    <p>29.63</p> Signup and view all the answers

    If the absolute value of the calculated t-value is larger than the critical value in a hypothesis test, what should be the decision?

    <p>Reject the null hypothesis.</p> Signup and view all the answers

    What does the notation H1: E[BMI] ≠ 25 signify in hypothesis testing?

    <p>The expected value of BMI is different from 25.</p> Signup and view all the answers

    What is the significance level used in the t-test example provided for BMI?

    <p>5%</p> Signup and view all the answers

    Which statistic is used to determine whether to reject the null hypothesis in a t-test?

    <p>t-value</p> Signup and view all the answers

    What data method is used in the example provided for wages in different years?

    <p>Pooled cross-sectional data</p> Signup and view all the answers

    What is a characteristic of the GSOEP sample from Germany?

    <p>It includes a representative sample of private households.</p> Signup and view all the answers

    Which scale of measurement describes realizations that can be ranked but have no meaningful differences?

    <p>Ordinal scale</p> Signup and view all the answers

    What type of data is represented by industry classes according to the data scale?

    <p>Nominal scale</p> Signup and view all the answers

    When were Eastern Germans added to the GSOEP sample?

    <p>1994/1995</p> Signup and view all the answers

    Which of the following best describes Cardinal/interval scale data?

    <p>Data expressed as multiples with meaningful intervals</p> Signup and view all the answers

    What kind of questions does the GSOEP survey include in the yearly changing topics?

    <p>Environmental behavior</p> Signup and view all the answers

    In the context of data maintenance, what can additional samples be used for?

    <p>To analyze only specific subgroups of the population</p> Signup and view all the answers

    What equation represents the confidence interval for the population mean when the population variance is unknown?

    <p>$P(X̄ - t_{α/2} · \frac{σ̂_X}{√N} ≤ µ_X ≤ X̄ + t_{α/2} · \frac{σ̂_X}{√N}) = 1 - α$</p> Signup and view all the answers

    When the expected value µ_X is unknown, which method is commonly used to estimate it?

    <p>Using the sample mean $X̄$.</p> Signup and view all the answers

    What is the main purpose of constructing a confidence interval?

    <p>To provide a range in which the population parameter likely lies.</p> Signup and view all the answers

    In a 95% confidence interval, which critical value is typically used?

    <p>1.96</p> Signup and view all the answers

    What happens to the confidence interval as the sample size N increases?

    <p>It becomes narrower.</p> Signup and view all the answers

    Which assumption is made when using the t-distribution to create a confidence interval?

    <p>The sample comes from a normally distributed population.</p> Signup and view all the answers

    Which formula represents the standardized sample mean when using the estimated variance?

    <p>$Z̄ = \frac{X̄ - µ_X}{(σ̂_X/√N)}$</p> Signup and view all the answers

    What does the symbol $t_{α/2}$ represent in the context of confidence intervals?

    <p>The critical value from the t-distribution.</p> Signup and view all the answers

    What happens to the variance of the sample mean as the number of observations increases?

    <p>It decreases and converges to zero.</p> Signup and view all the answers

    What is the formula used to calculate the unbiased estimator for the variance of a random variable?

    <p>$\hat{\sigma}<em>X^2 = \frac{1}{N-1} \sum</em>{i=1}^{N} (X_i - \bar{X})^2$</p> Signup and view all the answers

    What does $plim \bar{X} = E(X)$ signify in the context of the sample mean?

    <p>The sample mean converges to the expected value of the random variable.</p> Signup and view all the answers

    What is the role of degrees of freedom in the estimation of variance?

    <p>They adjust the estimate to account for the number of estimated parameters.</p> Signup and view all the answers

    In the formula for the variance of the sample mean, what does $N$ represent?

    <p>The sample size.</p> Signup and view all the answers

    Which statement about the average of a random variable is correct?

    <p>The average can converge to the expected value as sample size increases.</p> Signup and view all the answers

    What does the notation $\sigma_X^2$ represent?

    <p>The variance of the population distribution.</p> Signup and view all the answers

    How is the variance of a sample mean expressed in terms of the population variance?

    <p>$Var(\bar{X}) = \frac{\sigma_X^2}{N}$</p> Signup and view all the answers

    Study Notes

    Introductory Econometrics - Course Information

    • Course Instructor: Simon Martin
    • University: University of Vienna
    • Term: Winter 2024-25
    • Slides: Courtesy of Tomaso Duso (DIW Berlin), Martin Halla (WU Vienna), Liyang Sun (CEMFI), Jesse M. Shapiro (Harvard and NBER), and Andrea Weber (CEU). Based on Wooldridge (2022), and Pearson on Stock and Watson (2020).
    • Errors: All errors are the instructor's responsibility.

    Course Aims and Content

    • Understanding: Standard econometric methods.
    • Empirical Analysis: Modern empirical economic literature and performing one's own analysis of cross-sectional, time series, and panel data.
    • Methods: Includes Least Squares Estimation, Instrumental Variables Estimation, and Maximum Likelihood.
    • Target Audience: Master students in Applied Economics (913 [3]), Banking and Finance (974), Research in Economics and Finance (953 [1]), and Philosophy and Economics (642).
    • Prerequisites: Background in statistics, probability theory, mathematical statistics, and linear regression.

    Course Schedule and Materials

    Assignments and Evaluation

    • Attendance: Unexcused absence from the first session leads to deregistration. Notify instructor of absence in advance to remain in course.
    • Assessment:
      • 2 Tests (45% each) on November 15, 2024, and January 31, 2025 (each 60 minutes)
      • Homework assignments (2 exercises in groups of up to 4, for 5% each)
      • November 22nd and January 24th for homework due dates
      • Self-selected group submissions via Moodle
    • Retake Exam: Students who fail or miss a test are eligible for a retake on February 12, 2025. Registration by February 6, 2025. The worse of the two exams is replaced.

    Examples of Topics

    • Field Experiments: General procedure, treatment and control groups, random (or quasi-random) assignment
    • Policy Evaluation: Identify Agglomeration Spillovers (Greenstone, Hornbeck and Moretti 2010)
    • Cash Transfer Program in Kenya: Panel A. Uganda, Panel B. Kenya, data on age sets societies
    • Forecasting: Methods for heavily used analysis forecasting tools.

    Course Plan

    • Basic Econometric Tools: Linear regression model with single regressor, Multivariate regression, OLS estimator & its properties, Difference-in-difference, experiments, Problems with time series, Multicollinearity, heteroskedasticity, GLS, clustering, Panel data methods
    • Advanced Econometric Tools: Endogeneity and instrumental variables estimation (IV), Systems of Equations, Quasi-experiments, Maximum likelihood estimation, Discrete choice models, Sample selection, Advanced time series analysis, Forecasting, Dynamic causal effects
    • Unit 1: Introduction to estimation and testing

    Literature

    • Books: Stock, J. H., and Watson, M. W. (2020), Wooldridge, Jeffrey M.(2020), Angrist, J.D. and Pischke, J.-S. (2009), Cunningham, Scott (2021), Greene, W.H. (2019), Wooldridge (2010), Hanck, C., et al (2020), Heiss, F. (2020).

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    Introductory Econometrics PDF - Winter Term 2024-25

    Description

    This course aims to provide master students with a strong foundation in standard econometric methods. Participants will engage in empirical analysis of economic literature, working with various data types including cross-sectional, time series, and panel data. Core topics include Least Squares Estimation, Instrumental Variables, and Maximum Likelihood methods.

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