...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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...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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...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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...What is Econometrics? Econometrics is a rapidly developing branch of economics which, broadly speaking, aims to give empirical content to economic relations. The term ‘econometrics’ appears to have been first used by Pawel Ciompa as early as 1910; although it is Ragnar Frisch, one of the founders of the Econometric Society, who should be given the credit for coining the term, and for establishing it as a subject in the sense in which it is known today (see Frisch, 1936, p. 95). Econometrics can be defined generally as ‘the application of mathematics and statistical methods to the analysis of economic data’, or more precisely in the words of Samuelson, Koopmans and Stone (1954), ... as the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference (p. 142). Other similar descriptions of what econometrics entails can be found in the preface or the introduction to most texts in econometrics. Malinvaud (1966), for example, interprets econometrics broadly to include ‘every application of mathematics or of statistical methods to the study of economic phenomena’. Christ (1966) takes the objective of econometrics to be ‘the production of quantitative economic statements that either explain the behaviour of variables we have already seen, or forecast (i.e. predict) behaviour that we have not yet seen, or both’. Chow (1983) in a more recent textbook succinctly defines econometrics ‘as the...
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...ARTICLE IN PRESS Journal of Econometrics ] (]]]]) ]]]–]]] www.elsevier.com/locate/jeconom Modeling the diffusion of scientific publications Dennis Fok, Philip Hans Fransesà Econometric Institute, Erasmus University Rotterdam, P.O. Box 1738, NL-3000 DR Rotterdam, The Netherlands Abstract This paper illustrates that salient features of a panel of time series of annual citations can be captured by a Bass type diffusion model. We put forward an extended version of this diffusion model, where we consider the relation between key characteristics of the diffusion process and features of the articles. More specifically, parameters measuring citations’ ceiling and the timing of peak citations are correlated with specific features of the articles like the number of pages and the number of authors. Our approach amounts to a multi-level non-linear regression for a panel of time series. We illustrate our model for citations to articles that were published in Econometrica and the Journal of Econometrics. Amongst other things, we find that more references lead to more citations and that for the Journal of Econometrics peak citations of more recent articles tend to occur later. r 2006 Elsevier B.V. All rights reserved. JEL classification: C33; M21 Keywords: Diffusion of innovations; Multi-level regression 1. Introduction Citations to scientific publications like journal articles often show characteristics that bear similarities with the diffusion of a new product. Shortly after publication...
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...Financial Econometrics With Eviews Roman Kozhan Download free books at Roman Kozhan Financial Econometrics Download free eBooks at bookboon.com 2 Financial Econometrics – with EViews © 2010 Roman Kozhan & Ventus Publishing ApS ISBN 978-87-7681-427-4 To my wife Nataly Download free eBooks at bookboon.com 3 Contents Financial Econometrics Contents Preface 6 1 1.1 1.2 1.3 1.4 Introduction to EViews 6.0 Workfiles in EViews Objects Eviews Functions Programming in Eviews 7 8 10 18 22 2 2.1 2.2 2.3 Regression Model Introduction Linear Regression Model Nonlinear Regression 34 34 34 52 3 3.1 3.2 3.3 Univariate Time Series: Linear Models Introduction Stationarity and Autocorrelations ARMA processes 54 54 54 59 www.sylvania.com We do not reinvent the wheel we reinvent light. Fascinating lighting offers an infinite spectrum of possibilities: Innovative technologies and new markets provide both opportunities and challenges. An environment in which your expertise is in high demand. Enjoy the supportive working atmosphere within our global group and benefit from international career paths. Implement sustainable ideas in close cooperation with other specialists and contribute to influencing our future. Come and join us in reinventing light every day. Light is OSRAM Download free eBooks at bookboon.com 4 Click on the ad to read more Contents ...
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...TYPE OF DATA Times Series Data A time series is a sequence of data points, typically consisting of successive measurements made over a time interval. Examples of time series are ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. Time series are very frequently plotted via line charts. Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements Cross-Section Data Cross-sectional data, or a cross section of a study population, in statistics and econometrics is a type data collected by observing many subjects (such as individuals, firms, countries, or regions) at the same point of time, or without regard to differences in time. Analysis of cross-sectional data usually consists of comparing the differences among the subjects. For example, if we want to measure current obesity levels in a population, we could draw a sample of 1,000 people randomly from that population (also known as a cross section of that population), measure their weight and height, and calculate what percentage of that sample is categorized as obese. This cross-sectional sample provides us with a snapshot of that population, at that one point in time. Note that we do not know based...
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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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...A STUDY: INCOME AND HAPPINESS ACROSS EUROPE: DO REFERENCE VALUES MATTER? Contents Summary 2 The Silver Lining of Materialism: The Impact of Luxury Consumption on Subjective Well-Being 3 Data used for analysis 5 Econometric Model 6 Critical Reflection 8 Reference List 11 A Study: Income and happiness across Europe: Do reference values matter? Summary The authors in this study - Guglielmo Maria Caporale, Yannis Georgellis, Nicholas Tsitsianis and Ya Ping Yin - assess the relationship between income and subjective well-being; by tracing back to works of Adam Smith, Karl Marx, Veblen and Duesenberry, the authors revive significant attention to the neoclassical economic theory that portrays well-being and absolute income to be highly correlated. The data was retrieved from the European Social Survey (ESS) to examine a potential relationship between income and happiness (self-reported satisfaction), the authors execute their study across 19 European Countries. With utilisation of Easterlin (1974) as their seminal paper, the research draws attention to the Easterlin Paradox (Easterlin, 1995) that suggests there is no relationship between economic expansion in industrialised countries and its average level of happiness. The authors look to assess topical contradictory findings that conclude absolute income is correlated with levels of happiness (e.g.: Frijters et al., 2004). The research purpose of this paper was to re-examine this controversial link for...
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...h a p t e r One The Nature of Econometrics and Economic Data C hapter 1 discusses the scope of econometrics and raises general issues that result from the application of econometric methods. Section 1.3 examines the kinds of data sets that are used in business, economics, and other social sciences. Section 1.4 provides an intuitive discussion of the difficulties associated with the inference of causality in the social sciences. 1.1 WHAT IS ECONOMETRICS? Imagine that you are hired by your state government to evaluate the effectiveness of a publicly funded job training program. Suppose this program teaches workers various ways to use computers in the manufacturing process. The twenty-week program offers courses during nonworking hours. Any hourly manufacturing worker may participate, and enrollment in all or part of the program is voluntary. You are to determine what, if any, effect the training program has on each worker’s subsequent hourly wage. Now suppose you work for an investment bank. You are to study the returns on different investment strategies involving short-term U.S. treasury bills to decide whether they comply with implied economic theories. The task of answering such questions may seem daunting at first. At this point, you may only have a vague idea of the kind of data you would need to collect. By the end of this introductory econometrics course, you should know how to use econometric methods to formally evaluate a job training program...
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...empec, Vol. 13, 1988, page 223-249 Nonparametric Estimation and Hypothesis Testing in Econometric Models By A. Ullah ~ Abstract: In this paper we systematically review and develop nonparametric estimation and testing techniques in the context of econometric models. The results are discussed under the settings of regression model and kernel estimation, although as indicated in the paper these results can go through for other econometric models and for the nearest neighbor estimation. A nontechnical survey of the asymptotic properties of kernel regression estimation is also presented. The technique described in the paper are useful for the empirical analysis of the economic relations whose true functional forms are usually unknown. 1 Introduction Consider an economic model y =R(x)+u where y is a dependent variable, x is a vector o f regressors, u is the disturbance and R(x) = E ( y l x ) . Often, in practice, the estimation o f the derivatives o f R(x)are o f interest. For example, the first derivative indicates the response coefficient (regression coefficient) o f y with respect to x, and the second derivauve indicates the curvature o f R(x). In the parametric econometrics the estimation o f these derivatives and testing 1 Aman Ullah, Department of Economics, University of Western Ontario, London, Ontario, N6A 5C2, Canada. I thank L Ahmad, A. Bera, A. Pagan, C. Robinson, A. Zellner, and the participants of the workshops at the Universities of Chicago...
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...York University Faculty of Liberal Arts & Professional Studies Department of Economics Fall 2014 Course Outline Course # and Title: AP/ECON 4140 3.0A Financial Econometrics Course Webpage: http://www.yorku.ca/rsufana/teaching.htm Course Instructor/Contact: Name: Prof. Razvan Sufana Office: VH 1030 Phone: 416-736-2100 Ext. 66065 Office Hours: Tuesday 2 – 3 PM, Thursday 2:45 – 3:45 PM Email: rsufana@yorku.ca (Please include course number in subject line) LectureTime and Location: Thursday 11:30 – 2:30 PM, ACE 002 Prerequisite: AP/ECON 3210 3.00 or AP/ECON 3500 3.00 or equivalent. Course Credit Exclusions: None. PRIOR TO FALL 2009: Course credit exclusion: AK/ECON 4130 3.00. Course Description: This course is an introduction to financial econometrics. Background knowledge of finance is not required. The objective of the course is to explain, in simple terms, the use of selected statistical methods and econometric models in finance. The content of the course includes simple static and dynamic models of financial returns, elements of portfolio theory, the CAPM regression model, elements of option pricing, the Value-at-Risk (VaR), and the ARCH model. Weighting of Course: Assignment 1 (12.5% of final grade): available October 2, due at beginning of class on October 9 Midterm Exam (30% of final grade): October 16 Assignment 2 (12.5% of final grade): available November 20, ...
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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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