Assignment #1 (1)

docx

School

McMaster University *

*We aren’t endorsed by this school

Course

4F03

Subject

Economics

Date

Jan 9, 2024

Type

docx

Pages

2

Uploaded by SuperHumanLlamaMaster86

Report
Assignment # 1 Economics 4F03 Fall 2022 1. The following frequency tables have been prepared in STATA using the Survey of Labour and Income Dynamics (SLID) for the following variables: a) Assuming that all respondents in the sample are reported as either Male or Female, how many observations are there in total? - Male: 22,916 - Female: 24,789 - Therefore, in total there are 47,705 respondents b) How many failed to respond to the question about marital status? - 71 people c) How many failed to respond to the question about immigrant status? - 34,905 people 2. Summary statstcs for the following variables have been produced a) What is the average age of respondents in the sample? What is the minimum age? What is the variance of the age variable? - The average age of the respondents in the sample 48.1 - The minimum age is 16 - The variance of the age variable 335.23. b) What is the average wage? What is the maximum wage? What is the variance of the wage variable? - The average wage is 23.5 - The maximum wage is $187.2 - The variance of the wage variable is 194.357
3. Below is a Two-way table or cross-tabulation of sex and marital status. a) What evidence in the table suggests sex and marital status are not statistically independent? Statistical independence requires that the joint probability is the product of the marginal probabilities, e.g. from the table above, the marginal probabilities are: P(Male) = .4801, P(Widowed) = .0602. - P(AnB) is 0.011, P(A)0.4801 x P(B)0.0602=P(A)P(B)= 0.029. For two variables to be statically independent, P(AnB)= P(A)P(B). However, based on the calculations above 0.011 does not equal 0.029. b) Explain this evidence in a few sentences. I.e what may explain for the differences between the male distribution and the female distribution? - Women are more likely to be separated, widowed or divorced than men. On average, men get married later than women which showcases the fact that men do not get married young. On the other hand, women get married young and have a less greater life expectancy than men. 4. A Linear regression is estmated using hourly wage in dollars(imphwe1) as the dependent variable. Independent variables are a constant(cons), a person’s age in years(ecage26), and their years of work experience(yrxfte11). a) R-squared - 0.1033 roughly 10% of the variance in the hourly wage rate is determined through years of experience and age. Therefore, the other 90% of the variance may be determined by other factors which are missing in the data group such as income. b) Regression coeficients, including the constant. - 16.12 For a person of age 0 that has no experience, the hourly wage would be $16.12/ hour (constant) - 0.076 For every additional age, an addition of 7.6 cents/hour is added to the hourly wage rate - 0.268 for every additional year of experience, an addition of 26.8 cents/hour is added to the hourly wage rate c) Coeficient standard errors. - For a given mean of the distribution, if the error of the mean is comparable to the mean itself, then the estimate is probably not a good one. d) t statistics - The t-statistic showcases and examines the amount of standard errors the coefficient is away from 0. Any t-value greater than 2 or less than 2, in absolute values, is a good indicator since greater confidence levels come from higher t-values. 7.24 23.94 53.19 e) p-values (in the P>|t|) column - The data above showcases a confident rejection of the null hypothesis since the coefficients are equal to 0. f) 95% confidence intervals - These values showcase the true mean of the population within a 95% range. .0555472 .0967696 .2459602 .2898193 15.52841 16.71656
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help