...YOUR ECONOMETRICS PAPER BASIC TIPS There are a couple of websites that you can browse to give you some ideas for topics and data. Think about what you want to do with this paper. Econometrics is a great tool to market when looking for jobs. A well-written econometrics paper and your presentation can be a nice addition to your resume. You are not expected to do original research here. REPLICATION of prior results is perfectly acceptable. Read Studenmund's Chapter 11. One of the most frustrating things in doing an econometrics paper is finding the data. Do not spend a lot of time on a topic before determining whether there is data available that will allow you to answer your question. It is a good idea to write down your ideal data set that would allow you to address your topic. If you find that the available data is not even close to what you had originally desired, you might want to change your topic. Also, remember that knowing the location of your data – website, reference book, etc – is not the same as having your data available to use. It may take a LONG time to get the data in a format that EVIEWS can read. Do not leave this till the last minute. For most data, I enter the data into Excel first. I save the Excel sheet in the oldest version, namely MS Excel Worksheet 2.1 . The reason is that format can be read by most programs whereas newer formats may or may not be read. Eviews easily reads an Excel sheet 2.1 version. You should use the...
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...e YOUR ECONOMETRICS PAPER BASIC TIPS There are a couple of websites that you can browse to give you some ideas for topics and data. Think about what you want to do with this paper. Econometrics is a great tool to market when looking for jobs. A well-written econometrics paper and your presentation can be a nice addition to your resume. You are not expected to do original research here. REPLICATION of prior results is perfectly acceptable. Read Studenmund's Chapter 11. One of the most frustrating things in doing an econometrics paper is finding the data. Do not spend a lot of time on a topic before determining whether there is data available that will allow you to answer your question. It is a good idea to write down your ideal data set that would allow you to address your topic. If you find that the available data is not even close to what you had originally desired, you might want to change your topic. Also, remember that knowing the location of your data – website, reference book, etc – is not the same as having your data available to use. It may take a LONG time to get the data in a format that EVIEWS can read. Do not leave this till the last minute. For most data, I enter the data into Excel first. I save the Excel sheet in the oldest version, namely MS Excel Worksheet 2.1 . The reason is that format can be read by most programs whereas newer formats may or may not be read. Eviews easily reads an Excel sheet 2.1 version. You should use...
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...Econometrics (Economics 360) Syllabus: Spring 2015 Instructor: Ben Van Kammen Office: Krannert 531 Office Hours: Friday, 10 a.m.-noon Email: bvankamm@purdue.edu Meeting Location: KRAN G010 Meeting Days/Times: TR 1:30-2:45 p.m. (001) TR 3-4:15 p.m. (002) TR 4:30-5:45 p.m. (003) Course Description This is an upper division economics course required for students pursuing a BS in economics. It is one of the few courses that explicitly covers empirical methods, i.e., the analysis of observed economic behavior in the form of data. Empirics stand in contrast to theory, e.g., micro and macro, about how agents behave. Despite this under-representation, empirical analysis comprises a large part of economists’ workload and is one of the most practical skills that an economics student can learn. Course Objectives In this class students will: 1. perform statistical and practical inference based on the results of empirical analysis, 2. identify useful characteristics of estimators, e.g., unbiasedness, consistency, efficiency, 3. state predictions of theoretical economic models in terms of testable hypotheses, 4. model economic relationships using classical methods, such as Ordinary Least Squares, derive the properties of estimators related to these methods, and 5. perform estimation using methods discussed in class using software, 6. perform diagnostic tests that infer whether a model’s assumptions are invalid, 7. evaluate empirical models based on whether their resulting estimators...
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...Introduction The purpose of the project was to see if using futures contracts to hedge can reduce exposure to market risk over a period of time. This project covered both stock portfolios and bond portfolios. To illustrate this, the method of linear regression and least squares was used. We used linear regression to regress the spot rate against the futures contract return. To complete this project both EViews and Microsoft Excel was used. Summary of Points Stock Regression 2008-2009 Around 96% of the stock portfolio returns can be explained. This was calculated by finding the variance proportion, r2 in EViews. The high percentage suggests that our model is a strong fit for the data that was analyzed. We were also able to show that our estimated beta was reliably different than 0 and reliably different than 1. This was done through two-sided tests using a 95% significance level. The tcrit value was found using the excel function tinv() with 497 degrees of freedom. Testing for B=0, the t-statistic was 110.087, with the tcrit value being 1.964 this was a clear indication to reject the null because 110.087 is not in the range of -1.964 to 1.964. Testing for B=1, the t-statistic was -3.37853, with the tcrit value being 1.964 this was also a clear indication to reject the null because -3.37853 is not in the range of -1.964 to 1.964. After finding the optimal hedge ratio we calculated the dollar position for the futures market hedge to be $9,702,250. By using...
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...International Conference On Applied Economics – ICOAE 2010 299 DOES STOCK MARKET DEVELOPMENT CAUSE ECONOMIC GROWTH? A TIME SERIES ANALYSIS FOR BANGLADESH ECONOMY MD. SHARIF HOSSAIN (PH. D.)1 - KHND. MD. MOSTAFA KAMAL2 Abstract In this paper the principal purpose has been made to investigate the causal relationship between stock market development and economic growth in Bangladesh. To investigate long-run causal linkages between stock market development and economic growth the Engle-Granger causality and ML tests are applied. In this paper another attempt has been made to investigate the non-stationarity in the series of stock market development and economic growth by using modern econometric techniques. The co-integrated tests are applied to know whether this pair of variables shares the same stochastic trend or not. From our analysis it has been found that the stock market development strongly influences the economic growth in Bangladesh economy, but there is no causation from economic growth to stock market development. Thus unidirectional causality has prevailed between stock market development and economic growth in the Bangladesh economy. Also it has been found that all the variables are integrated of order 1, and both the variables stock market development and economic growth share the same stochastic trend in Bangladesh economy. JEL Code: C010 Key Words: Stock Market Development, Causal Relationship, Non-stationarity, Unit Root Test, Co-integrated Tests 1 ...
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...AND COMMENTS TO Joy de Beyer ( jdebeyer@worldbank.org) and Ayda Yurekli (ayurekli@worldbank.org) World Bank, MSN G7-702 1818 H Street NW Washington DC, 20433 USA Fax : (202) 522-3234 Contents I. Introduction 1 Purpose of this Tool 1 Who Should Use this Tool 2 How to Use this Tool 2 II. Define the Objectives of the Analysis 4 The Reason for Analysis of Demand 4 The Economic Case for Demand Intervention 4 Analysis of Demand for the Policy Maker 5 Design an Analysis of Demand Study 6 Components of a Study 6 The Nature of Econometric Analysis 7 Resources Required 7 Summary 8 References and Additional Information 8 III. Conduct Background Research 9 IV. Build the Data Set 11 Choose the Variables 11 Data Availability 11 Data Types 12 Prepare the Data 13 Data Cleaning and Preliminary Examination 14 Preparing the Data Variables 14 References and Additional Information 19 V. Choose the Demand Model 20 Determine the Identification Problem 20 Test for Price Endogeneity 21 ...
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...This page intentionally left blank Introductory Econometrics for Finance SECOND EDITION This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. It includes examples and case studies which finance students will recognise and relate to. This new edition builds on the successful data- and problem-driven approach of the first edition, giving students the skills to estimate and interpret models while developing an intuitive grasp of underlying theoretical concepts. Key features: ● Thoroughly revised and updated, including two new chapters on ● ● ● ● ● ● panel data and limited dependent variable models Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models Detailed examples and case studies from finance show students how techniques are applied in real research Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods Thoroughly class-tested in leading finance schools Chris Brooks is Professor of Finance at the ICMA Centre, University...
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...CHAPTER ONE 1.1 INTRODUCTION A casual look at the published empirical work in business and econometric will reveal that many economic relationships are of single –equation type. In such models, one variable (the dependent variable Y) is expressed as a linear function of one or more other variables (the explanatory variables, the X’s). An implicit assumption is that the cause and effect relationship, if any , between Y and X’s is unidirectional. The explanatory variables are the cause and the dependent variable is the effect . However, there are situations where there is a two- way or simultaneous relationships between Y and some of the X’s which makes the distinction between the dependent and the explanatory variables of dubious value. It is better to lump together a set of variables that can be determined simultaneously by the remaining set of variables- precisely what is done in simultaneous equation models. In such models, there is more than one equation - one for each of the mutually or jointly dependent or endogenous variables. And unlike the single equation models, in the simultaneous equation models, one may estimate the parameters of a single equation without taking into account information provided by the other equation in the system. In a simultaneous equation system, variables that appear only on the right – hand side of the equation are called exogenous or predetermined variables. They are truly independent or non-stochastic because they remain fixed. Variables...
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...Donau-City-Strasse 1, A-1220 Vienna, Austria. Author for correspondence. E-mail: thomas.roediger@arcs.ac.at a Abstract. During the past 20 years, the world pharmaceutical industry has experienced a dramatic increase in R&D intensity. We apply and extend a model developed by Grabowski and Vernon (2000, Journal of Evolutionary Economics, 10, 201–215) with a pooled data sample of the 15 publicly listed Japanese drug firms for the period 1987– 1998. As in the original study, we find expected returns to be an important determinant of R&D spending in the Japanese drug industry, albeit considerably smaller than in the U.S., which is particularly obvious in the case of returns from newly introduced drugs. However, our results are sensitive to econometric model specification, in particular to controlling for serial correlation and to a dynamic specification of the baseline model. Likewise, estimates on financial constraints are sensitive to model specification, indicating that Japanese drug firms face small or no financial constraints. Our results are consistent with the general literature on R&D investment behaviour, yet raise some methodological questions with regard to the original study. Key words: investment, Japan, panel data estimation, pharmaceuticals, R&D. JEL Classifications: L65, O31, O33. I. Introduction During the past 20 years, the world pharmaceutical industry has experienced a dramatic increase in R&D intensity. In a recent paper, Grabowski and Vernon (2000) explore the...
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...This page intentionally left blank Introductory Econometrics for Finance SECOND EDITION This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. It includes examples and case studies which finance students will recognise and relate to. This new edition builds on the successful data- and problem-driven approach of the first edition, giving students the skills to estimate and interpret models while developing an intuitive grasp of underlying theoretical concepts. Key features: ● Thoroughly revised and updated, including two new chapters on ● ● ● ● ● ● panel data and limited dependent variable models Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models Detailed examples and case studies from finance show students how techniques are applied in real research Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods Thoroughly class-tested in leading finance schools Chris Brooks is Professor of Finance...
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...Mostly Harmless Econometrics: An Empiricist’ Companion s Joshua D. Angrist Massachusetts Institute of Technology Jörn-Ste¤en Pischke The London School of Economics March 2008 ii Contents Preface Acknowledgments Organization of this Book xi xiii xv I Introduction 1 3 9 10 12 16 1 Questions about Questions 2 The Experimental Ideal 2.1 2.2 2.3 The Selection Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Random Assignment Solves the Selection Problem . . . . . . . . . . . . . . . . . . . . . . . . Regression Analysis of Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II The Core 19 21 22 23 26 30 36 38 38 44 47 51 51 3 Making Regression Make Sense 3.1 Regression Fundamentals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 3.1.2 3.1.3 3.1.4 3.2 Economic Relationships and the Conditional Expectation Function . . . . . . . . . . . Linear Regression and the CEF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Asymptotic OLS Inference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saturated Models, Main E¤ects, and Other Regression Talk . . . . . . . . . . . . . . . Regression and Causality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 3.2.2 3.2.3 The Conditional Independence Assumption . . . . . . . . . . . . . . . . . . . . . . . . The Omitted Variables Bias Formula . ....
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...ELECTRICITY CONSUMPTION AND ECONOMIC GROWTH IN NIGERIA: NEW INSIGHTS INTO THE CAUSALITY RELATIONSHIP AN ECONOMETRICS ASSIGNMENT SUBMITTED BY ------------------------------------------------- OLUWAFEMI JOSHUA IBRAHIM MATRIC NUMBER: 121937 LEVEL: 700 LECTURER IN-CHARGE: PROFESSOR E.O. OGUNKOLA November, 2010 1) STATEMENT OF THE PROBLEM Electricity plays a very important role in the socio-economic and technological development of every nation. It is widely accepted that there is a strong correlation between socio-economic development and the availability of electricity (Sambo, 2008). It is generally recognized that energy, including electricity, plays a significant role in economic development, not only because it enhances the productivity of capital , labour and other factors of production, but also that increased consumption, particularly commercial energy like electricity, signifies high economic status of a country(Aklas & Yilmaz, 2008). The relationship that exists between electricity consumption and economic growth has been of great interest to many researchers. The study of this relationship arises from the need to understand the complex links between these variables. Such understanding is basic to regulators and investors in deregulated electricity markets, in order to design a system that is reliable, efficient and growth-efficient. The empirical argument has been centered on whether economic growth responds to increase in electricity consumption, or whether...
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...Seminar Financial Risk Management 20011-2012 Erasmus University Testing the validity of Purchasing Power Parity: In time series and panel analysis using CPI, TPI and PPI. Supervisor: Everaert Gerdie Leonora Jean-Timothy Marsoufandis-Balomenos Nikolaos Venieris Michael February 10th, 2012 319006 356941 354890 Abstract The examination of the Purchasing power parity theory with reference to 22 (invluding the U.S) countries is the prime objective of the paper. Consumer price index (CPI), whole sale price/producer price index (PPI), traded price index (TPI) and nominal exchange rate are the variables which were investigated in this study for the period 1957Q1-1998Q4, on the basis of the mean reversion hypothesis. Engle-Granger co-integration and Unit root tests have been employed to both of variables and estimated residuals of the sample in order to test the purchasing power parity. Keywords: Purchasing Power Parity, unit-root and co-integration. Content 1. Introduction……………………………………………………………….….3 2. Literature review………………………………………………………….….4 3. Data……………………………………………………………………………7 4. Methodology………………………………………………………………….8 5. Empirical results………………………………………………………..…....11 5.1. 5.2. 5.3. 5.4. 5.5. Unit-root and cointegration results(CPI)……………………………....11 Unit-root and co-integration results(TPI)……………………………..15 Unit-root and co-integration results(PPI)……………………………..16 Half-life deviations from PPP…………………………………………..17 Forecast performance…………………………………………………...20 6....
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...Project of Econometrics INTRODUCTION In this paper our motivation to discuss effects of models by estimating its parameters in matrix and scalar notations, its variances checked via different formal and informal methods, checked the depends of error terms and analyze that auto-correlation whether it is positive, zero or negative, we also check the data is normality distributed or not, and check the structural stability. We consider the civilian unemployment rate and manufacturing hourly compensation in US dollars for simple regression. We consider the data in multiple regressions on Wildcat activity. Wildcats are wells drilled to find and produce oil and gas in an improved area or to find a new reservoir in a field previously found to be productive of oil or gas or to extend the limit of a known oil or gas reservoir. For hetroscedasticity tests we consider for simple regression wholesale and consumer price index data and for multiple regressions we take same data which we above used for multiple regression. We consider Fertility and other data for 64 countries for the F-test, Durbin-Watson test and CHOW test where child mortality depends upon the female literacy rate, per capita GNP and total fertility rate. DATA SOURCES I took the data from the Guajarati book. Table 5.10 on page no. 158 represents the data which we used for simple regression for hetroscedasticity tests. Table 7.7on page no. 237 represents the data which I used for multiple regressions. Table 6.4...
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...Foreign direct investment And Economic Growth in Bangladesh Internship program at Brac Bank Ltd. Internship Report On “Foreign direct investment And Economic Growth in Bangladesh and Internship program at Brac Bank Ltd.” The Internship report is submitted to the Department of Finance, University of Dhaka for the partial fulfillment of the requirement of BBA program. Submitted to: Department of Finance University of Dhaka Supervised by: Mohammad Jahangir Alam Chowdhury Professor Department of Finance University of Dhaka Submitted by: Zarin Tasnim ID: 17-009 Section: A Department of Finance University of Dhaka Signature of the Supervisor Date of Submission: 7th May, 2015 Letter of Transmittal 7th May, 2015 Mohammad Jahangir Alam Chowdhury Professor Department of Finance University of Dhaka Subject: Submission of Internship Report on Foreign direct investment and Economic Growth in Bangladesh. Dear Sir, It is an absolute pleasure for me to submit the Internship Report titled “Foreign direct investment and Economic Growth in Bangladesh” as a significant part of the BBA program. While making this report, I have experienced a fair knowledge about Foreign direct investment and economy of Bangladesh and its impact on the growth of Bangladesh. I have tried my best to follow your guidelines in every aspect of preparing this report. I have collected what I believed...
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