Economics 774: Winter 2016 Syllabus: Project Expectations / Guidelines

Transcription

1 Economics 774: Winter 2016 Syllabus: Project Expectations / Guidelines Goals of this Course: 1. To develop a policy relevant research question 2. To explain the research question and put it into an economic framework that is understandable by a broad community. 3. To develop a working data set with which to study the research question. 4. To develop an empirical analysis of the question. The empirical analysis will capture data set development, strengths and weaknesses of the data, broad statistics/pictures/etc that describe the data and the core measures, and a statistical analysis of the measure that seeks to answer the research question and to provide a policy context for understanding the implications of the results of the analysis. Also included in this part of the course is the development of tables, graphs, figures. 5. To write well organized, logical, and documented programs using STATA. It is important to learn the programming language, to understand commands, and to efficiently use the commands. 6. To develop a policy report that explains the research question, an economic framework for thinking about the question, the data set used to analyze the question, and the empirical analysis. This piece must be developed for non-academics (general policy community) and includes both a written paper and a presentation at the end of the course. These goals will be achieved by your working on your own. However, I strongly encourage working with other students in the course to explore ideas, use of stata, data analysis techniques. Grading Scheme: Late submissions will be penalized 5% of the mark per day Motivation for Project: Due Feb 26 th, 4 pm 10% Stata code (do files, log files used to create your working data set) and memo describing data development: Due March 21 st, 4 pm 30% Policy Presentation: Week of May 9th 30% Note that presentation will be evaluated on style (10%) and content (20%)) Policy Report: Due May 20 th, 4 pm 30% Note that the report will be evaluated both on content, depth of analysis, logic/organization of report, and on grammar (writing/exposition: 10%; analysis: 20%) Project Description: Below are a list of ideas which you are expected to refine into a specific question that will be studied. These ideas have been developed based on the data available for your use in the PEDAL laboratory. You will find it easiest to create a project based on these ideas. You may, however, seek permission to study a different question, provided you have proven to me that the data are available, these data are put into PEDAL no later than February 22nd, and that these data meet the expectations for developing a policy report for this course. If you choose to select your own question, note that you must provide to me, in writing, no later than February 12 th, a description of the question you are going to study, a justification of why your question is suitable for study in the MAEP program, and a detailed description of each data set you have obtained and how the data sets will be linked. The first step to working on your project is to submit your project motivation. The grade on your project motivation must receive a score of 7 or better to be considered approved. If you receive a score of less than 7 you will be expected to resubmit the project motivation in order to 1

2 continue with your project for the course. Projects will be allocated based on the best articulation of the question you are studying, an economic motivation for your question, and why the data are suitable for your question. Note that for many of the ideas presented below it is anticipated there will be one question developed per idea. Students may not work on identical ideas unless it is shown that the questions developed and/or the data used for the questions are sufficiently distinct to permit distinct projects. If your motivation looks to be the same as another student, the student with the best articulated motivation will be approved. If your motivation is not the best motivation, you will have one week to resubmit a new motivation. Expectations for a well written Project Motivation: a clearly written one page abstract that captures the novelty and importance of what you are studying. Evaluation will be based on your ability to succinctly and clearly motivate your question, to explain why that question has a policy relevance, to explain the economic underpinnings of your question (e.g. what is the economic framework for thinking about the question), and the core set of measures that will be studied (e.g. the dependent variables and main independent variables). The motivation should be no more than 1 page, single space, 12 point font and 1 inch margins. Data for Project: You will be given access to partially transformed data housed in the Public Economics Data Analysis Laboratory. As part of the project you will be expected to develop a working data set using these data and from the collection of information from other sources. My evaluation of the working data set will be based on the programs used to develop the working data set, a memo that describes the development of the working data set, and your working data set. Stata Training: You must use stata to build your data sets and your analyses. All work must be completed by creating do files (programs). Conducting an interactive development of data and analysis is not acceptable (e.g. not creating a series of do files for data set development and analysis). As part of the course, we are offering a self-graded stata test on Monday January 18 th to assess your stata skills. You are responsible for ensuring you have the training necessary to complete 774. To assist in this training, we are offering training sessions on January 25 th, February 1 st, and February 8 th. While these are optional, we strongly encourage your participating in these sessions. Your work on the project officially starts the week after reading week. You are permitted to start work as soon as you like, however. You may submit your project motivation as soon as you like. If you submit the motivation prior to the due date, expect it to take me 4-5 days to provide you with your mark and feedback. Project Development: Lectures are designed to guide you through your data development and analysis. You will be broken up into two groups. Typically each group will meet once per week. Each week you should come to lecture and pass around a one page memorandum that will identify: (a) your goals for the previous week, (b) what you accomplished, (c) the current hurdles you are facing, and (d) your plans for addressing these hurdles. While these lectures are optional, you are responsible for all training and discussions undertaken during these lectures. I use the lectures to promote good practices around your project development. Note that failure to attend lectures can easily result in your not satisfactorily developing a data set and/or project that meets the requirements of this course. This is a course where you should work on your project throughout the term. Expectations for Policy Presentation: Details on the policy presentation will be provided closer to the date of the presentation. The expectations, however, are that you can clearly explain the big picture 2

3 policy question you are trying to address, the specific question you are studying, how we should think about that question in an economic framework, the development of your data set, your preliminary and statistical analysis, and then how your analysis helps to inform policy. Expectations for Policy Report: You are writing a report that is for a general audience. Thus the report should not look like an academic paper. I strongly encourage you to work off an outline that you develop throughout the term. The report should look like a report you might find being issued by a think tank (e.g. CD Howe, Higher Education Quality Council of Ontario, U. of Calgary School of Public Policy reports, etc.). Your report not only will motivate the policy issue well but will be careful in discussing the economic framework for the question under study and the development of your data set, and will tell a story using tables, graphs/figures, and more robust statistical analysis. Meeting Times February: 22 nd /23 rd : Individual meetings to discuss your project and your plan for completing the project. February 29 th /March 1 st : Group meetings begin. I will send you an to let you know your assigned group. Group 1 will meet on Mondays; Group 2 will meet on Tuesdays. Use of PEDAL: Please note that you may not remove the data from PEDAL. You are expected to use PEDAL to develop your project. Any removal of data without permission will be considered academic dishonesty and will be addressed as per the rules of the university around academic dishonesty. This can include automatic failure of the course. The deadlines for submission of assignments are designed to ensure timely and successful completion of your policy project. If you leave this project to the last minute you will not complete it and you will risk failing the course! Project Ideas 1. Umbrella Giving.. Benefits and Costs. In many communities, individuals can donate to an organization whose responsibility is to distribute those donations to local charities to support the services provided by the charities. We tend to call these organizations umbrella organizations. There are several types of umbrella organizations and they operate slightly differently. These organizations include: the United Way, Community Foundations, and the Salvation Army. One might ask why an individual should donate to an umbrella organization instead of the organization directly. One might also ask whether the organizations that receive funding from the umbrella organization are better off than organizations that do not receive funding. This idea could result in a several projects. a. One approach might be to focus on a study of a particular type of umbrella organization funding and how that funding has changed over time and what factors contribute to a community embracing (or not embracing) the use of umbrella organizations. The primary data used for this project would include the charity T3010 data set which captures the financial records of all registered charities in Canada from the mid-1990s to the present. These data would be linked to other data which could include data on reported tax-receipted giving at a neighbourhood level which could be rolled up to the same community level as captured by umbrella agencies. b. A second approach might be to focus on the potential competition across umbrella organizations in a community and to consider what factors explain the growth/decline of 3

4 one type of umbrella organization v. another type of umbrella organization. The primary data used for this project would also be the T3010 data set capturing the financial records of all registered charities in Canada from the mid-1990s. c. A third approach might to study the charities that receive funding from umbrella organizations and to consider how this type of funding supports promotes or detracts from a stable stream of revenue and/or program service provision. The primary data used for this project would be the T3010 data set but would involve using information from the foundation part of the data sets to identify the charities that receive or do not receive funding from umbrella groups. 2. Is there a value to applying to lots of university programs? In the late 1990s, students were given an opportunity to apply to more than 3 programs when applying to university in Ontario. In general, the application process is such that a student pays a flat fee that permits the student to apply to 3 programs. If the student wants to apply to more than 3 programs, the student must then pay an additional fee. Does having more choice at the application stage matter? Why should it matter? The primary data for this idea are the data from the Ontario University Application Centre (1990s to the present). These data contain the records for every application to university via the direct entry route (from an Ontario high school to the university). You can observe high school grades, high school attended, program & university of application, and program & university of registration. 3. In Ontario, university tuitions are highly regulated while there is some differentiation in tuition and program fees across universities and program types, the range in these fees is fairly tight (prove this!). Does this lead to students receiving similar educations across universities? If so, what is the value of attending one university over another. There has been some conversation in Ontario that universities should be able to specialize and differentiate themselves. This is a debate going on in Australia and other countries. We already observe this differentiation in the U.S. and other countries (e.g. what happens in the UK). There are arguments for requiring universities to charge the same rates and there are arguments for permitting universities to charge different rates. What should be done in Ontario? For this idea, I would suggest exploring the degree to which student enrollment varies across universities based on observed ability (high school grades). It may be useful to compare groups of students based on observed skills/ability (e.g. math & science v. non-math/science) with their choices in registration. We sometimes thing that geography plays a big role in registration how much of registration is tied to geography and how much is tied to skill/ability? Your primary data source would be the Ontario University Application Centre data. a. A second project using this idea would be to consider potential implications for students residing in low income neighbourhoods if universities can differentiate and charge tuitions that are less regulated than what currently is permitted. 4. Food is sometimes considered one of the first predictors of poverty. Think about it.. you re running low on money, what is going to give.. rent, food, transportation to work? Charities are active in the support of food needs of individuals and families. Charities can vary in their delivery sometimes it is a food basket (e.g. food bank), sometimes it is a hot meal, or other type of provision. Does the type of service delivery matter? Why should it matter? This idea would involve using the T3010 data on charity finances to explore the different types of food related services being provided and then to link this information to some source of information tied to poverty like measures. One option might be to link charities providing food related 4

5 services to data on household income based on individual tax returns filed with the Canada Revenue Agency. a. An analogous project might be constructed by focusing on the types of service delivery for housing matters. b. A third project might be constructed by focusing on the types of service delivery related to employment. Another approach might be to focus on provincial goals around poverty reduction. There could be a comparison of approaches across 2 or more provinces with a focus on studying how charitable service provision affects the achievement of these goals. Alternatively, one could focus on a particular province and looks at towns/cities in that province. With this idea you likely would want to focus on particular aspects of service provision that are related to poverty (e.g. housing, food, shelter). 5. Across the provinces, the tax benefits for donating to charity has changed a few times since the 1990s (the start of our data). Charities raise funds a few different ways. One is to ask for direct donations from individuals, permitting the individual to claim the donation on her tax return. This results in a credit against tax liability, effectively reducing the price of giving. A second form of charity fundraising, however, is to host or participate in special events that raises revenues for the charity but also means that the contributor does not receive a credit for supporting the charity e.g. if one purchases a lottery ticket for a charity draw, the value of the lottery ticket can not be claimed back as a donation. The idea for this project is to consider how changes in tax credits affect charities fundraising efforts, specifically the revenues received by a charity as revenue from its fundraising efforts. The main source of data for this project is the T3010 charity information return. 6. There are well over 85,000 registered charities in Canada. Most of these charities are small with very low annual revenues. So what makes a big charity big? Regardless of size, some charities appear sustainable whereas others seem to consistently be on the brink of closure. Ignoring big charities such as hospital foundations, universities, those operating outside of Canada, churches, and the like using the T3010 data (described above), this idea is to understand better the determinants of big charities. One approach would be to identify a set of charities that open during the period of data coverage and explore differences in growth patterns to formulate a testable hypothesis. Another approach would be to explore some sort of arguably exogenous change that would lead to some charities with similar service provisions to grow in some areas but not in other areas. Overall, the idea is to understand better the factors that support sustainable operations. a. One project might focus on organizations that rely mostly on private giving. b. Another project might focus on organizations that rely mostly on government funding. 7. If you look across Hamilton, or other small-medium sized cities, you will find high schools where students are doing well and high schools where students are not doing well (can use EQAO grade 9 test score to demonstrate this), there is variation in the share of students applying to university, and variation in the types of university programs attended (by those students that go onto university). Focusing on schools that might be considered high risk for students not staying in high school and/or not going onto post-secondary education, what do we know about the students that do pursue a university education (using the university application data). What are strong correlates that explain differences in university attendance across high 5

6 schools. For this project you will have to construct a way of identifying high risk high schools and create a sample of schools across different communities. a. A second project could focus on what we know about high schools that have higher v. lower risk students based on linking grade 6 and grade 9 eqao scores and exploring differences in the sorting of students based on grade 6 test scores into high schools. b. A third project could focus on identifying at risk students based on information from grade 3 test scores and then to follow them onto grade 6 and grade 9 to understand why some low performing students at grade 3 recover while others do not. 8. What is the relationship between grade 11 and grade 12 course selections? Relative to the overall cost of a post-secondary educational degree, the cost of applying to university as well as the cost of applying to several programs seems relatively trivial. Recent research, however, suggests that application costs may make a difference. In Ontario, there have been several periods of changes in the cost of applying to university. The first big change was the change that permitted students to apply to more than three programs. Beyond that there have been various changes around the costs of applying to university. In this project you will want to develop a question that pertains to understanding the relationship between grade 11 and grade 12 course selections and performance for university applicants. NOTE I have designed this project that it will require a high level of technical skills and ability to program and use Stata (and possibly other programs). Main source of data: Applications to university in Ontario for 10+ years. 6

7 Description of Data Sets in PEDAL for use in projects 1. T3010 Charity Information Return: Several data sets capturing the revenues/expenses/+ other information for all registered charities in Canada from mid-1990s to present (2014). We are making available to you the data from 2005 to 2014 unless earlier years are requested. Data captured from tax (information) returns filed by each charity. The forms have changed several times over the period so not all measures will be available for all years. There is a base data set plus several other data sets that capture other information (e.g. for more recent years amounts distributed to other charities, information on board members). You can go online to see the current forms to understand better the types of information captured on the returns. 2. Individual/household tax return data at the forward sortation area (FSA) level (first 3 characters of the postal code) aggregated data on income, charitable donations reported on the individual tax returns. 3. Census measures (socio-demographic-economic) for neighbourhoods delineated by FSA (see above for definition) and dissemination area (see statistics Canada for definition/how constructed) for census years 1991, 1996, 2001, 2006, EQAO student based test scores for grades 3, 6, and 9 (linked for later years and unlinked for all years) 1998 to present for Ontario. For each student you know the test score, if took the test, school assigned, gender, and a few other individual characteristics 5. School level information all Ontario schools 1990s to present. Captures location, board assignment, type of school, and enrollment by grade and gender 6. University application information for students applying to university directly from an Ontario high school: mid 1990s to present. Includes information on high school of student, gender of student, age of student, grades in courses in level 3 & 4 high school courses, programs & university of application and program & university of registration. 7