...Statistics and Econometrics Mid-Term – Bank Loan Default I. Introduction The question requires us to understand what factors could lead to people defaulting on their loans. The variables that will be discussed include age, education, employment, address, income etc. An overview of the data will be provided along with assessing inter-relationships among variables as well as providing a good fit model. II. Overview of Data The sample includes 700 observations in the data set based on the summary. Below is the list of variables and the mean, minimum, maximum of the data. The average age of the people in the sample data is 34.86 or 35 years. The minimum is 20 years whereas the maximum age in the group is 56 years. The average level of education is 1.72 or 2 years. The minimum is 1 year and maximum is 5 years of education in the sample. The average years that a person stays with their current employer are 8.38 years. The minimum is 0 years and the maximum is 31 years with the employer. The average years that a person stays at their current address is 8.27 years. The minimum is 0 years and the maximum that someone will stay at their current address is 34 years. The average household income in thousands is 45.60. The minimum household income in the sample is 14 and the maximum is 446 thousand dollars. The average debt to income ratio (x100) is 10.26. The minimum debt to income in the sample is 0.4 whereas the maximum ratio was 41.3. The...
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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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...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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...Journal of Economic Literature Vol. XXXIV (March 1996), pp. 97-114 The Standard Error of Regressions By D E I R D R E N . M C C L O S K E Y and STEPHEN T. ZILIAK University of Iowa Suggestions by two anonymous and patient referees greatly improved the paper. Our thanks also to seminars at Clark, Iowa State, Harvard, Houston, Indiana, and Kansas State universities, at Williatns College, and at the universities of Virginia and Iowa. A colleague at Iowa, Calvin Siehert, was materially helpful. T cant for science or policy and yet be insignificant statistically, ignored by the less thoughtful researchers. In the 1930s Jerzy Neyman and Egon S. Pearson, and then more explicitly Abraham Wald, argued that actual investigations should depend on substantive not merely statistical significance. In 1933 Neyman and Pearson wrote of type I and type II errors: HE IDEA OF Statistical significance is old, as old as Cicero writing on forecasts (Cicero, De Divinatione, 1. xiii. 23). In 1773 Laplace used it to test whether comets came from outside the solar system (Elizabeth Scott 1953, p. 20). The first use of the very word "significance" in a statistical context seems to be John Venn's, in 1888, speaking of differences expressed in units of probable error; Is it more serious to convict an innocent man or to acquit a guilty? That will depend on the consequences of the error; is the punishment death or fine; what is the danger to the community of released...
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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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...EXECUTIVE SUMMARY. A case study seeks to associate with reward and employee motivation and identify association between employee motivation and employee motivation variables for instance gender, age, education, and income level and job experience in banking in Pakistan. The study should be based on primary data and sample size, by use of questionnaires. The partners are, therefore, in case of a business opportunity should apply relevant entrepreneurial skills in order to succeed especially by following the following path. Two hypotheses were developed for the present study and were tested by using Chi-square Test and binary Regression Test. The result of Chi-square shows that P- value is 0.048 of Chi-square its mean there is an association between salary and gender. The correlation between rewards and Employee Motivation is 0.546, which shows the positive relationship between compensation and employee motivation Payment structure is a crucial element in a business plan and should be carefully be looked into for instance the partners should make sure that they recruit a reasonable number of workers that they are able to manage. Objectives of this study (i).To determine if there is an association between rewards and employee motivation, biographical factors (Gender, age, education, qualification, and Income level). (ii).To identify the types of reward system in Pakistani Banks. (iii).To determine the impacts of rewards system on Banks employees’ biographical variables. (iv)...
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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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...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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...Goethe University Frankfurt Advanced Econometrics 2, Part 2 Sommersemester 2016 Prof. Michael Binder, Ph.D. I. Vector Autoregressions and Vector Error Correction Models 3. Estimation and Inference with and without Parameter Restrictions Cointegrated VAR – Case of a Single Cointegrating Relationship Special Case of One Cointegrating Relationship: Weak Exogeneity and ARDL Models When the cointegration rank of a cointegrated VAR is one, then under certain conditions it is feasible to work with a notably more parsimonious model, namely the so-called Autoregressive Distributed Lag (ARDL) model of the form: p q 1 − ∑ φ j Lj yt =∑ θ j ' xt − j + ε t , = 1= 0 j j iid ( (76) ) with ε t ~ 0, σ 2 . Note: For simplicity of notation only, in (76) model deterministic components are irgnored and it is assumed that all elements of x enter with the same lag order, namely q. 68 Goethe University Frankfurt Advanced Econometrics 2, Part 2 Sommersemester 2016 Prof. Michael Binder, Ph.D. I. Vector Autoregressions and Vector Error Correction Models 3. Estimation and Inference with and without Parameter Restrictions Cointegrated VAR – Case of a Single Cointegrating Relationship To understand when we can reduce a cointegrated VAR to an ARDL model, let us carefully derive the ARDL model in (76) from a system of equations in zt = ( yt xt )′ . Suppose zt is generated by { } p j εt , I − ∑ Φ j L zt = j =1 (77) iid t = 1, 2,..., T , with ε t ~ ( 0, Ω ) . We assume that...
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...CURRICLUM VITAE PROFESSOR ABDULRAZZAK CHARBAJI Date and Place of Birth: Beirut 7-25-1948 Nationality: Lebanese Sex: Male Marital Status: Married Address: P.O.Box: 11- 2065 Riad El Solh Beirut 11072100 Lebanon. Land Line: 961 - 1 - 355046 Mobile 961 - 3 - 714279 E-mail: Prof., charbaji@charbaji.com Computer Skills: Econometrics Eviews, SPSS, Advanced SPSS, Excel and Microsoft Project. EDUCATION: Year 1978 Degree Ph.D. Institution Univ. of Northern Colorado Department of Applied Statistics & Research Methods Univ. of Northern Colorado. U.S.A http://www.unco.edu Univ. of Northern Colorado. U.S.A Beirut Arab University Area of Study Applied Statistics & Research Methods http://www.unco.edu/coe/asr m/programs.htm http://www.unco.edu/coe/asr m/index.htm Business Administration/ Financial Management Commerce/Economics 1975 1971 M.A. B.A. Published Research In International Referred Journals: " The Effect of Globalization on Commitment to Ethical Corporate Governance and Corporate Social Responsibility in Lebanon”, Social Responsibility Journal (2009). http://www.emeraldinsight.com.ezproxy.aub.edu.lb/Insight/viewContainer.do;jsessionid=F8 FECFB1ECF1459573B900E5DE0A6B28?containerType=Journal&containerId=6000003 "Assessing the Global Readiness of Arab Countries to Join the WTO: A Multivaraite analysis" Journal of Economic & Administrative Sciences (JEAS) Vol. 24, No. 1, June 2008 (1 - 14). http://jeas.cbe.uaeu.ac.ae/jeas2008_Jun/01_Assess.pdf http//:jeas.cbe.uaeu.ac...
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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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...Question 1: Conceptual Question (a) Model I: The major econometric issue is on the error term ui. The equation ui2=γ1+γ2x1,j indicates that the error term ui is related with the independent variable x1. Under the general assumptions, the error term us designed to capture ‘unexpected’ events, as such the error term should be random and the independent variable x1 is not random which means that its value if known. Therefore, model I breaks out this assumption, the error term ui is related with the independent variable x1 (not random), error term uiwill hence be not random as well. As a result, the dependent variable y will be not random which is wrong in econometrics. (b) Model II: The major econometric issue is on the error term vt. The equation vt=ρvt-1 indicates that for the pair of random error term vt and vt-1, there is linear association among them. Under the fourth assumption of the simple linear regression model, the covariance between any pair of random errors is zero, implying that there is no linear association among them. Therefore, model II breaks out this assumption, one random error term vt has a linear relationship with another random error term vt-1. (c) Model III: The major econometric issue is on the independent variable x1,i. x1,i~i.i.d(ux, σx2) indicates that x1,i is independent and identically distributed random variables. Under the fifth assumption of the simple linear regression model, it requires the regressors x1,i to...
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...yr.) in Statistics Email: biplab.stat@gmail.com Mathematics & Statistics Department Contact no: +91 8670327205 Indian Institute of Technology Kanpur D.O.B-11.10.1989 EDUCATIONAL QUALIFICATIONS Relevant Course: Regression Analysis, Time Series analysis, Analysis of Variance, Statistical & AI Data mining, Stochastic Processes , Linear Programming and Extensions , Computer Programming and Data structure, Econometrics, Economics Problem & policy, Multivariate Analysis , Sampling Theory , Game theory. EDUCATIONAL ACHIEVEMENTS & WORK EXPERIENCE: ϖ secured All India Rank 229 in the Joint Admission to M.Sc. (JAM) examination (2010). ❖ Application of ARCH, GARCH model Abstract: GARCH model has been used to understand and model large variability of the adjusted closing prices of S&P 500 index under Dr .Amit Mitra, Dept. of Mathematics & Statistics, IIT Kanpur ❖ Analyzing factors effecting crime rate Abstract: Analysis on how different causes effect crime rate of U.S.A using appropriate regression model. The areas covered are multicollinearity, variable selection, and residual analysis under Dr. Sharmishta Mitra, Dept. of Mathematics & Statistics, IIT Kanpur. ϖ Study of Short term Labor market statistics in OECD Countries using PCA, Classification tree & regression tree, clustering under Dr Amit Mitra. ϖStudy of GDP as a function of its components and lags using Econometrics approach...
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...Does Saving really matter for Growth in Developing Countries? The Case of a Small Open Economy Olajide S. Oladipo, PhD Department of Economics and Finance School of Business, Medgar Evers College 1637 Bedford Avenue, Brooklyn, NY 11225 Email: ooladipo@ mec.cuny.edu Abstract The study employed the Toda and Yamamoto (1995) and Dolado and Lutkepohl (1996) – TYDL- methodology to uncover the direction of causal relationship between savings and economic growth in Nigeria between 1970 and 2006. The empirical results suggest that savings and economic growth are positively cointegrated indicating a stable long run equilibrium relationship. Further, the findings revealed a unidirectional causality between savings and economic growth and the complementary role of FDI in growth. Keywords: Cointegration, FDI, Savings and Economic Growth JEL Classification: C32; E21;O11 Does Saving really matter for Growth in Developing Countries? The Case of a Small Open Economy Introduction The relationship between savings and economic growth has received increased attention in recent years especially in developed and emerging economies [see Bacha (1990), DeGregorio (1992), Levine and Renelt (1992), and Jappelli and Pagano (1994)]. This might not be unconnected to the central underpinning of Lewis’s (1955) traditional development theory that increasing savings would accelerate economic growth. Research efforts by Kaldor (1956) and Samuelson and Modigliani (1966) examined how different savings...
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