hw2neil - Econ M134 UCLA Spring 2010 Prof. Kahn Homework #2...

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Econ M134 UCLA Spring 2010 Prof. Kahn Homework #2 Due in Class, Wednesday, April 14 Environmental Kuznets Curve This assignment is intended to explore the "Environmental Kuznets Curve", (henceforth EKC) we have learned about in class. See Chapter 3 of Kahn’s Green Cities. We are going to explore the relationship between income, population, and pollution in cities. Pollution will be proxied for using a city’s level of PM10. PM10 represent small particulate matter. Public health research has documented that exposure to PM10 raises morbidity and mortality risk (see http://en.wikipedia.org/wiki/Particulate). Additionally this assignment will serve as an introduction to statistical estimation using STATA. STATA is available in many computer labs around campus; to find the most convenient lab for your schedule visit this webpage: http://www.computerlabs.ucla.edu/Info.asp Additionally you may access STATA remotely from your home computer; visit this webpage for more information on remote access: http://computing.sscnet.ucla.edu/public/services/remoteaccess.aspx For those of you who may already have a copy of STATA on your home computer, any edition at or above STATA 7.0 will be acceptable for completing this assignment. You can also use any other statistics program, such as R, which is available for free. Some of the questions can be done in Microsoft Excel. If you need help be aware that Neil only knows how to use STATA. You may form a study group of up to four people per group. Each group will only need to hand in one assignment. Please write all students' names and students' ID numbers on the homework. If possible, please type up your answers. Longer is not better, keep your answers brief and to the point. Read the entire assignment, and be sure to follow the directions. 1. Download the data file called pm10b.dta from the course website, and open the data file using STATA. If you are not using STATA the data is saved as comma separated values pmb10.txt or as an excel spreadsheet in pmb10.xls. The data includes 5 variables: Variable Description Country Country of Origin City City Name pop2000 City Population in 2000 pm10 City ambient particulate matter Rgdpl Country real per-capita GDP rgdpl2 (Per-Capita GDP) 2 Pop20002 (Population) 2
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Answer the following questions: (a) Are there more rich or poor cities in the dataset? (Hint: make a histogram of real gdp) (b) Are there more dirty or clean cities in the dataset? (Hint: make a histogram of pm10) (c) How does pollution depend on GDP in the dataset? (Hint: plot pm10 versus GDP) 2. Estimate a regression of city ambient pollution on city population, city population squared, real GDP, and real GDP squared, without a constant. (the command to do this in STATA is: reg pm10 pop2000 rgdpl rgdpl2, nocon ). Report the results in a nice table and answer the following questions. (a) Write out the regression like an equation (e.g. grade=a+b*studying+ε, where ε is the random
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This note was uploaded on 11/12/2010 for the course ECON M134 taught by Professor Bresnock during the Spring '08 term at UCLA.

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hw2neil - Econ M134 UCLA Spring 2010 Prof. Kahn Homework #2...

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