Future Poverty Level: What Do You Expect To See Happening?

Future Poverty Level1 What Do You Expect To See Happening With The Po

What do you expect to see happening with the poverty level in the future? Notes from class The Poverty Rate A commonly used gauge of the distribution of income is the poverty rate. The poverty rate is the percentage of the population whose family income falls below an absolute level called the poverty line. The poverty line is set by the federal government at roughly three times the cost of providing an adequate diet. This line is adjusted every year to account for changes in the level of prices, and it depends on family size.

To get some idea about what the poverty rate tells us, consider the data for 2008. In that year, the median family had an income of $61,521, and the poverty line for a family of four was $22,025. The poverty rate was 13.2 percent. In other words, 13.2 percent of the population were members of families with incomes below the poverty line for their family size. Policies to Reduce Poverty As we have just seen, political philosophers hold various views about what role the government should take in altering the distribution of income.

Political debate among the larger population of voters reflects a similar disagreement. Despite these continuing debates, most people believe that, at the very least, the government should try to help those most in need. According to a popular metaphor, the government should provide a “safety net” to prevent any citizen from falling too far. Poverty is one of the most difficult problems that policymakers face. Poor families are more likely than the overall population to experience homelessness, drug dependence, health problems, teenage pregnancy, illiteracy, unemployment, and low educational attainment.

Members of poor families are both more likely to commit crimes and more likely to be victims of crimes. Although it is hard to separate the causes of poverty from the effects, there is no doubt that poverty is associated with various economic and social ills. Suppose that you were a policymaker in the government, and your goal was to reduce the number of people living in poverty. How would you achieve this goal? Here we examine some of the policy options that you might consider.

Each of these options helps some people escape poverty, but none of them is perfect, and deciding upon the best combination to use is not easy. Minimum-Wage Laws Laws setting a minimum wage that employers can pay workers are a perennial source of debate. Advocates view the minimum wage as a way of helping the working poor without any cost to the government. Critics view it as hurting those it is intended to help. The minimum wage is easily understood using the tools of supply and demand, as we first saw in Chapter 6.

For workers with low levels of skill and experience, a high minimum wage forces the wage above the level that balances supply and demand. It therefore raises the cost of labor to firms and reduces the quantity of labor that those firms demand. The result is higher unemployment among those groups of workers affected by the minimum wage. Those workers who remain employed benefit from a higher wage, but those who might have been employed at a lower wage are worse off. The magnitude of these effects depends crucially on the elasticity of demand.

Advocates of a high minimum wage argue that the demand for unskilled labor is relatively inelastic so that a high minimum wage depresses employment only slightly. Critics of the minimum wage argue that labor demand is more elastic, especially in the long run when firms can adjust employment and production more fully. They also note that many minimum-wage workers are teenagers from middle-class families so that a high minimum wage is imperfectly targeted as a policy for helping the poor. Welfare One way for the government to raise the living standards of the poor is to supplement their incomes. The primary way the government does this is through the welfare system.

Welfare is a broad term that encompasses various government programs. Temporary Assistance for Needy Families (TANF) is a program that assists families with children and no adult able to support the family. In a typical family receiving such assistance, the father is absent, and the mother is at home raising small children. Another welfare program is Supplemental Security Income (SSI), which provides assistance to the poor who are sick or disabled. Note that for both of these welfare programs, a poor person cannot qualify for assistance simply by having a low income.

He or she must also establish some additional “need,” such as small children or a disability. Negative Income Tax Whenever the government chooses a system to collect taxes, it affects the distribution of income. This is clearly true in the case of a progressive income tax, whereby high-income families pay a larger percentage of their income in taxes than do low-income families. As we discussed in Chapter 12, equity across income groups is an important criterion in the design of a tax system. Many economists have advocated supplementing the income of the poor using a negative income tax.

According to this policy, every family would report its income to the government. High-income families would pay a tax based on their incomes. Low-income families would receive a subsidy. In other words, they would “pay” a “negative tax.” Data ID Sal Compa Mid Age EES SER G Raise Deg Gen1 Gr ..7 0 M E The ongoing question that the weekly assignments will focus on is: Are males and females paid the same for equal work (under the Equal Pay Act)? ..9 0 M B Note: to simplify the analysis, we will assume that jobs within each grade comprise equal work. ..6 1 F B ..5 1 M E The column labels in the table mean: ..7 1 M D ID – Employee sample number Sal – Salary in thousands ..5 1 M F Age – Age in years EES – Appraisal rating (Employee evaluation score) ..7 1 F C SER – Years of service G – Gender (0 = male, 1 = female) ..8 1 F A Mid – salary grade midpoint Raise – percent of last raise.

M F Grade – job/pay grade Deg (0= BS\BA 1 = MS) ..7 1 F A Gen1 (Male or Female) Compa - salary divided by midpoint, a measure of salary that removes the impact of grade ..8 1 F A ..5 0 M E This data should be treated as a sample of employees taken from a company that has about 1,..7 0 F C employees using a random sampling approach. . F A ..9 1 F A ..7 0 M C Mac Users: The homework in this course assumes students have Windows Excel, and . F E can load the Analysis ToolPak into their version of Excel. ..6 0 F B The analysis tool pak has been removed from Excel for Windows, but a free third-party ..6 1 M A tool that can be used (found on an answers Microsoft site) is: ..8 0 F B ..3 1 M F Like the Microsoft site, I make cannot guarantee the program, but do know that ..8 1 F D Statplus is a respected statistical package.

You may use other approaches or tools ..3 0 F A as desired to complete the assignments. ..8 0 F D . M A ..2 0 F A ..9 1 M C ..4 0 F F ..4 0 M F ..3 0 M D ..9 1 F A ..6 0 M B ..5 1 M E ..9 1 M B ..3 0 F A ..3 0 F A ..2 0 F A ..5 0 M E ..5 0 F B ..3 0 M A ..3 0 M C ..7 1 F A ..5 0 F F ..2 1 M E ..2 1 F D ..9 1 M E ..5 1 M E ..3 1 F E ..6 0 M E ..6 0 M E Week 1 Week 1. Describing the data. 1 Using the Excel Analysis ToolPak function descriptive statistics, generate and show the descriptive statistics for each appropriate variable in the sample data set. a. For which variables in the data set does this function not work correctly for? Why? 2 Sort the data by Gen or Gen 1 (into males and females) and find the mean and standard deviation for each gender for the following variables: sal, compa, age, sr and raise. Use either the descriptive stats function or the Fx functions (average and stdev). 3 What is the probability for a: a. Randomly selected person being a male in grade E? b. Randomly selected male being in grade E? c. Why are the results different? 4 Find: a. The z score for each male salary, based on only the male salaries. b. The z score for each female salary, based on only the female salaries. c. The z score for each female compa, based on only the female compa values. d. The z score for each male compa, based on only the male compa values. e. What do the distributions and spread suggest about male and female salaries? Why might we want to use compa to measure salaries between males and females? 5 Based on this sample, what conclusions can you make about the issue of male and female pay equality? Are all of the results consistent with your conclusion? If not, why not? Week 2 Week 2 Testing means with the t-test For questions 2 and 3 below, be sure to list the null and alternate hypothesis statements. Use .05 for your significance level in making your decisions. For full credit, you need to also show the statistical outcomes - either the Excel test result or the calculations you performed. 1 Below are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean. Based on our sample, how do you interpret the results and what do these results suggest about the population means for male and female salaries? Males Females Ho: Mean salary = 45 Ho: Mean salary = 45 Ha: Mean salary =/= 45 Ha: Mean salary =/= 45 Note when performing a one sample test with ANOVA, the second variable (Ho) is listed as the same value for every corresponding value in the data set. t-Test: Two-Sample Assuming Unequal Variances t-Test: Two-Sample Assuming Unequal Variances Since the Ho variable has Var = 0, variances are unequal; this test defaults to 1 sample t in this situation Male Ho Female Ho Mean Mean Variance Variance 334. Observations Observations Hypothesized Mean Difference 0 Hypothesized Mean Difference 0 df 24 df 24 t Stat 1. t Stat -1. P(T For questions 3 and 4 below, be sure to list the null and alternate hypothesis statements. Use .05 for your significance level in making your decisions. For full credit, you need to also show the statistical outcomes - either the Excel test result or the calculations you performed. 1. Based on the sample data, can the average (mean) salary in the population be the same for each of the grade levels? (Assume equal variance, and use the analysis ToolPak function ANOVA.) Set up the input table/range to use as follows: Put all of the salary values for each grade under the appropriate grade label. Be sure to include the null and alternate hypothesis along with the statistical test and result. A B C D E F Note: Assume equal variances for all grades. 2. The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results. Grade Gender A B C D E F M The salary values were randomly picked for each cell. F Ho: Average salaries are equal for all grades Ha: Average salaries are not equal for all grades Ho: Average salaries by gender are equal Ha: Average salaries by gender are not equal Ho: Interaction is not significant Ha: Interaction is significant Perform analysis: Anova: Two-Factor With Replication SUMMARY A B C D E F Total M Count Sum Average 24.5 27.5 43..5 46. Variance 0.5 0.5 24... F Count Sum Total Count Sum Average Variance Total Count Sum Variance 23...5 50..25 Variance 1...... Note: a number with an E after it (E9 or E-6, for example) means we move the decimal point that number of places. Within .75 For example, 1.2E4 becomes 12000; while 4.56E-5 becomes 0. Total 8087. Do we reject or not reject each of the null hypotheses? What do your conclusions mean about the population values being tested? Interpretation: 3. Using our sample results, can we say that the compa values in the population are equal by grade and/or gender, and are independent of each factor? Grade Be sure to include the null and alternate hypothesis along with the statistical test and result. Gender A B C D E F Conduct and show the results of a 2-way ANOVA with replication using the completed table above. The results should look something like those in question 2. Interpret the results. Are the average compas for each gender (listed as sample) equal? For each grade? Do grade and gender interaction impact compa values? 4. Pick any other variable you are interested in and do a simple 2-way ANOVA without replication. Why did you pick this variable and what do the results show? Variable name: Be sure to include the null and alternate hypothesis along with the statistical test and result. Variable: F 5. Using the results for this week, what are your conclusions about gender equal pay for equal work at this point?