Group 1: Agus, E., Belisario, T., Bayaga, B. (Feb. 22, 2010)
The Effects of Carbon Dioxide Emissions and Energy Consumption on Economic Growth in the Philippines, 1980-2009
Group 2: Lee, D. Claveria, M. (Feb. 22, 2010)
Total Trade, Public Debt and Foreign Direct Investments in the Philippines, 1990-2009
Group 3: Hiloma, C., Wong, O. (Feb. 26, 2010)
Extent of Influence of Inflation and Interest Rates on Stock Return of the Philippine Stock Exchange, 2000-2009
Group 4: Braceros, L., Peralta, K., Tan, A. (Feb. 26, 2009)
Unemployment Rate in the Philippines and Its Determinants, 1990-2009
Group 5: Chua, J., Pascua, J., Chua, J. (Mar. 01, 2010)
Exchange Rate Volatility, Trade Openness and Political Stability in the Philippines, 1990-2009
Group 6: Rancio, T., Morales, Y., Vitor, A. (Mar. 01, 2010)
Poverty, Population, and Economic Growth in the Philippines: An Econometric Analysis
ECONOMETRICS PAPER
Outline of your econometric paper should be:
The front page
Give the title of the paper, your name, the date of production and the name of your professor. Also include an abstract of no more than 50 words. Do NOT produce a table of contents!.
Introduction
This is the place to present the basic problem of the paper. Try to give the motivation why this problem is so important. Also explain what the interested reader might learn from your work: who should be interested in the results? At the end of this section briefly describe the contents that will follow in the next section.
Review of the Literature
Your problem is not new. Summarize the relevant literature. The best thing to do is to identify key concepts in this literature you are interested in that you want the reader to remember. In this overview at least the papers that motivated you need to be mentioned. It is extremely important to note that you do not need to review all literature, only the stuff you think that is relevant.
The Model
If you use a model (either a formal mathematical model or a statistical model or a more conceptual model), explain it clearly. Be brief, keep it simple, and don't use inessential jargon. After that, formulate the key hypotheses.
The Data
Describe the data and sources of the data and your reservations concerning the data. The success of any econometric study hinges on the quality, as well as the quantity, of data. Fortunately, the Internet has opened up a veritable wealth of data.
Results
Explain the statistical methods you use. Present the results and link the outcomes with the hypotheses you formulated. Give more formal tests if required.
Conclusions
Give a very, very, very short conclusions. These conclusions can include policy advise, food for further thought (possible extensions) and the limitations of the analysis.
References
Produce a consistent list of references. Referencing is a discipline on its own. There are two basic rules: consistence and completeness. There needs to be a one-to-one match between references in the text and the list of literature used in the end. Depending on the publication-type use a consistent referencing at the end of the paper. Give the full set of references in alphabetical order of the last name of the first author. The reference format should follow the Harvard Style of Referencing.
Download the sample paper here!
The front page
Give the title of the paper, your name, the date of production and the name of your professor. Also include an abstract of no more than 50 words. Do NOT produce a table of contents!.
Introduction
This is the place to present the basic problem of the paper. Try to give the motivation why this problem is so important. Also explain what the interested reader might learn from your work: who should be interested in the results? At the end of this section briefly describe the contents that will follow in the next section.
Review of the Literature
Your problem is not new. Summarize the relevant literature. The best thing to do is to identify key concepts in this literature you are interested in that you want the reader to remember. In this overview at least the papers that motivated you need to be mentioned. It is extremely important to note that you do not need to review all literature, only the stuff you think that is relevant.
The Model
If you use a model (either a formal mathematical model or a statistical model or a more conceptual model), explain it clearly. Be brief, keep it simple, and don't use inessential jargon. After that, formulate the key hypotheses.
The Data
Describe the data and sources of the data and your reservations concerning the data. The success of any econometric study hinges on the quality, as well as the quantity, of data. Fortunately, the Internet has opened up a veritable wealth of data.
Results
Explain the statistical methods you use. Present the results and link the outcomes with the hypotheses you formulated. Give more formal tests if required.
Conclusions
Give a very, very, very short conclusions. These conclusions can include policy advise, food for further thought (possible extensions) and the limitations of the analysis.
References
Produce a consistent list of references. Referencing is a discipline on its own. There are two basic rules: consistence and completeness. There needs to be a one-to-one match between references in the text and the list of literature used in the end. Depending on the publication-type use a consistent referencing at the end of the paper. Give the full set of references in alphabetical order of the last name of the first author. The reference format should follow the Harvard Style of Referencing.
Download the sample paper here!
Syllabus
Course Description
This course focuses on learning and practicing basic econometrics with emphasis on the practice and less emphasis on deep econometric theory. Econometrics is a subfield of the economics discipline that mixes together economic theory, statistics and mathematics. The main purposes of the course are to introduce econometric theory at a very basic level and to let you apply the methods with the use of real world data.
The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics and related fields. Accordingly, the emphasis of the course is on empirical applications. The mathematics of econometrics will be introduced only as needed and will not be a central focus.
The applied work will be performed using econometric software package called EViews 4.1 Student Version software. Alternative econometric software packages (gretl, JMulti, and X-12-ARIMA) can also be downloaded for free at http://basiceconometrics.blogspot.com/.
Course Requirements
Periodically, the instructor will post news and information in the class blogspot. Students are responsible for ensuring that they will check daily this web page. The homework and the empirical project should be worked on groups of no more than three students. These groups should make a presentation of their results in the last week of the semester. Midterm and final examinations will be administered. Exams will cover all the topics discussed in class plus the techniques applied in homework assignments.
Attendance will be part of the grade. For each class missed students will loss 10% of the grade assigned for attendance. Students could miss two classes without justification.
Homework assignments will be available in the blogspot. The schedule for the due dates of each assignment will be announced in class and posted on the blogspot.
Students should be able to complete an empirical work applying the econometric tools presented in class. Groups have to define an economic or business issue, find the data to test it and finally apply the econometric tools to explain their hypothesis. Further information about the requirements for the paper will be provided in the class blogspot.
Academic Integrity
Working together is a wonderful way to learn, and your instructor encourages it. You will be encouraged to work with others in this class on any activity except examinations. All examinations, whether in-class or take-home, must be individual efforts. Plagiarism is taking someone else’s work and passing it off as your own. Plagiarism includes taking phrases, sentences, or paragraphs from someone else’s writing and using them in your own writing without providing true attribution of their source. Avoiding plagiarism, of course, does not mean neglecting to conduct solid research. It is appropriate to read what various scholars and experts have learned about an issue before you form your own conclusions about it.
However, you must ensure that you understand the literature. At a minimum, students should rephrase the literature’s content, rather than quoting it verbatim. This practice also helps to ensure student understanding of the issue, as you cannot write intelligently unless you do know your subject. Another way to avoid plagiarism is to ensure that you utilize a large number of sources, so that your knowledge goes beyond that of any particular book or article.
Classroom Etiquette
Students are expected to remain polite during classroom discussions. Even during heated debates, you must treat your classmates with respect. Violation of this policy will result in a reduction of your class participation grade. For example, you should not make derogatory remarks about your classmates’ ideas. Instead, explain why you think they are wrong, backing up your viewpoint with sound economic analysis and refrain from personal attacks. Another example is being quiet while someone else (including your instructor!) has the floor.
You may not use cellular telephones in class. If you bring them to class, they must be turned off. If there is an emergency situation that requires you to have an active telephone in class, you must notify your instructor in advance begins that your equipment will be turned on. In such cases, cell phones, if possible should be set to vibrate, not to sound an alarm.
Course Outline
PART ONE INTRODUCTION AND REVIEW
Chapter 1 Economic Questions and Data
1.1 Economic Questions We Examine
1.2 Causal Effects and Idealized Experiments
1.3 Data: Sources and Types
Chapter 2 Review of Probability
2.1 Random Variables and Probability Distributions
2.2 Expected Values, Mean, and Variance
2.3 Two Random Variables
2.4 The Normal, Chi-Squared, Student t, and F Distributions
2.5 Random Sampling and the Distribution of the Sample Average
2.6 Large-Sample Approximations to Sampling Distributions
Chapter 3 Review of Statistics
3.1 Estimation of the Population Mean
3.2 Hypothesis Tests Concerning the Population Mean
3.3 Confidence Intervals for the Population Mean
3.4 Comparing Means from Different Populations
3.5 Differences-of-Means Estimation of Causal Effects
3.6 Using the t-Statistic When the Sample Size Is Small
3.7 Scatterplot, the Sample Covariance, and the Sample Correlation Using Experimental Data
PART TWO FUNDAMENTALS OF REGRESSION ANALYSIS
Chapter 4 Linear Regression with One Regressor
4.1 The Linear Regression Model
4.2 Estimating the Coefficients of the Linear Regression Model
4.3 Measures of Fit
4.5 The Sampling Distribution of the OLS Estimators
4.6 Conclusion
Chapter 5 Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
5.1 Testing Hypotheses About One of the Regression Coefficients
5.2 Confidence Intervals for a Regression Coefficient
5.3 Regression When X Is a Binary Variable
5.5 The Theoretical Foundations of Ordinary Least Squares
5.5 The Theoretical Foundations of Ordinary Least Squares
5.6 Using the t-Statistic in Regression When the Sample Size Is Small
5.7 Conclusion
Chapter 6 Linear Regression with Multiple Regressors
6.1 Omitted Variable Bias
6.2 The Multiple Regression Model
6.3 The OLS Estimator in Multiple Regression
6.4 Measures of Fit in Multiple Regression
6.5 The Least Squares Assumptions in Multiple Regression
6.6 The Distribution of the OLS Estimators
6.7 Multicollinearity
6.8 Conclusion
Chapter 7 Hypothesis Tests and Confidence Intervals in Multiple Regression
7.1 Hypothesis Tests and Confidence Intervals for a Single Coefficient
7.2 Tests of Joint Hypotheses
7.3 Testing Single Restrictions Involving Multiple Coefficients
7.4 Confidence Sets for Multiple Coefficients
7.6 Analysis of the Test Score Data Set
7.7 Conclusion
Chapter 8 Nonlinear Regression Functions
8.1 A General Strategy for Modeling Nonlinear Regression Functions
8.2 Nonlinear Functions of a Single Independent Variable
8.4 Nonlinear Effects on Test Scores of the Student–Teacher Ratio
8.5 Conclusion
Chapter 9 Assessing Studies Based on Multiple Regression
9.1 Internal and External Validity
9.2 Threats to Internal Validity of Multiple Regression Analysis
9.3 Internal and External Validity When the Regression Is Used for Forecasting
9.4 Example: Test Scores and Class Size
9.5 Conclusion
Chapter 10 Conducting a Regression Study Using Economic Data
10.1 Choosing a Topic
10.2 Collecting the Data
10.3 Conducting Your Regression Analysis
10.4 Writing Up Your Results
This course focuses on learning and practicing basic econometrics with emphasis on the practice and less emphasis on deep econometric theory. Econometrics is a subfield of the economics discipline that mixes together economic theory, statistics and mathematics. The main purposes of the course are to introduce econometric theory at a very basic level and to let you apply the methods with the use of real world data.
The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics and related fields. Accordingly, the emphasis of the course is on empirical applications. The mathematics of econometrics will be introduced only as needed and will not be a central focus.
The applied work will be performed using econometric software package called EViews 4.1 Student Version software. Alternative econometric software packages (gretl, JMulti, and X-12-ARIMA) can also be downloaded for free at http://basiceconometrics.blogspot.com/.
Course Requirements
Periodically, the instructor will post news and information in the class blogspot. Students are responsible for ensuring that they will check daily this web page. The homework and the empirical project should be worked on groups of no more than three students. These groups should make a presentation of their results in the last week of the semester. Midterm and final examinations will be administered. Exams will cover all the topics discussed in class plus the techniques applied in homework assignments.
Attendance will be part of the grade. For each class missed students will loss 10% of the grade assigned for attendance. Students could miss two classes without justification.
Homework assignments will be available in the blogspot. The schedule for the due dates of each assignment will be announced in class and posted on the blogspot.
Students should be able to complete an empirical work applying the econometric tools presented in class. Groups have to define an economic or business issue, find the data to test it and finally apply the econometric tools to explain their hypothesis. Further information about the requirements for the paper will be provided in the class blogspot.
Academic Integrity
Working together is a wonderful way to learn, and your instructor encourages it. You will be encouraged to work with others in this class on any activity except examinations. All examinations, whether in-class or take-home, must be individual efforts. Plagiarism is taking someone else’s work and passing it off as your own. Plagiarism includes taking phrases, sentences, or paragraphs from someone else’s writing and using them in your own writing without providing true attribution of their source. Avoiding plagiarism, of course, does not mean neglecting to conduct solid research. It is appropriate to read what various scholars and experts have learned about an issue before you form your own conclusions about it.
However, you must ensure that you understand the literature. At a minimum, students should rephrase the literature’s content, rather than quoting it verbatim. This practice also helps to ensure student understanding of the issue, as you cannot write intelligently unless you do know your subject. Another way to avoid plagiarism is to ensure that you utilize a large number of sources, so that your knowledge goes beyond that of any particular book or article.
Classroom Etiquette
Students are expected to remain polite during classroom discussions. Even during heated debates, you must treat your classmates with respect. Violation of this policy will result in a reduction of your class participation grade. For example, you should not make derogatory remarks about your classmates’ ideas. Instead, explain why you think they are wrong, backing up your viewpoint with sound economic analysis and refrain from personal attacks. Another example is being quiet while someone else (including your instructor!) has the floor.
You may not use cellular telephones in class. If you bring them to class, they must be turned off. If there is an emergency situation that requires you to have an active telephone in class, you must notify your instructor in advance begins that your equipment will be turned on. In such cases, cell phones, if possible should be set to vibrate, not to sound an alarm.
Course Outline
PART ONE INTRODUCTION AND REVIEW
Chapter 1 Economic Questions and Data
1.1 Economic Questions We Examine
1.2 Causal Effects and Idealized Experiments
1.3 Data: Sources and Types
Chapter 2 Review of Probability
2.1 Random Variables and Probability Distributions
2.2 Expected Values, Mean, and Variance
2.3 Two Random Variables
2.4 The Normal, Chi-Squared, Student t, and F Distributions
2.5 Random Sampling and the Distribution of the Sample Average
2.6 Large-Sample Approximations to Sampling Distributions
Chapter 3 Review of Statistics
3.1 Estimation of the Population Mean
3.2 Hypothesis Tests Concerning the Population Mean
3.3 Confidence Intervals for the Population Mean
3.4 Comparing Means from Different Populations
3.5 Differences-of-Means Estimation of Causal Effects
3.6 Using the t-Statistic When the Sample Size Is Small
3.7 Scatterplot, the Sample Covariance, and the Sample Correlation Using Experimental Data
PART TWO FUNDAMENTALS OF REGRESSION ANALYSIS
Chapter 4 Linear Regression with One Regressor
4.1 The Linear Regression Model
4.2 Estimating the Coefficients of the Linear Regression Model
4.3 Measures of Fit
4.5 The Sampling Distribution of the OLS Estimators
4.6 Conclusion
Chapter 5 Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals
5.1 Testing Hypotheses About One of the Regression Coefficients
5.2 Confidence Intervals for a Regression Coefficient
5.3 Regression When X Is a Binary Variable
5.5 The Theoretical Foundations of Ordinary Least Squares
5.5 The Theoretical Foundations of Ordinary Least Squares
5.6 Using the t-Statistic in Regression When the Sample Size Is Small
5.7 Conclusion
Chapter 6 Linear Regression with Multiple Regressors
6.1 Omitted Variable Bias
6.2 The Multiple Regression Model
6.3 The OLS Estimator in Multiple Regression
6.4 Measures of Fit in Multiple Regression
6.5 The Least Squares Assumptions in Multiple Regression
6.6 The Distribution of the OLS Estimators
6.7 Multicollinearity
6.8 Conclusion
Chapter 7 Hypothesis Tests and Confidence Intervals in Multiple Regression
7.1 Hypothesis Tests and Confidence Intervals for a Single Coefficient
7.2 Tests of Joint Hypotheses
7.3 Testing Single Restrictions Involving Multiple Coefficients
7.4 Confidence Sets for Multiple Coefficients
7.6 Analysis of the Test Score Data Set
7.7 Conclusion
Chapter 8 Nonlinear Regression Functions
8.1 A General Strategy for Modeling Nonlinear Regression Functions
8.2 Nonlinear Functions of a Single Independent Variable
8.4 Nonlinear Effects on Test Scores of the Student–Teacher Ratio
8.5 Conclusion
Chapter 9 Assessing Studies Based on Multiple Regression
9.1 Internal and External Validity
9.2 Threats to Internal Validity of Multiple Regression Analysis
9.3 Internal and External Validity When the Regression Is Used for Forecasting
9.4 Example: Test Scores and Class Size
9.5 Conclusion
Chapter 10 Conducting a Regression Study Using Economic Data
10.1 Choosing a Topic
10.2 Collecting the Data
10.3 Conducting Your Regression Analysis
10.4 Writing Up Your Results
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