Abstract This paper is to employ a vector autoregressive model to investigate the impact of stock market and saving rate on GDP growth. The result indicates that the lagged values of both stock index and saving rate don’t have influence on the current value of GDP. However‚ we find that the lagged value of stock index does have impact on saving rate. We conclude that one of the most important reason lead to this result should due to small sample size and data of saving rate still remains non-stationary
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Abstract In this paper we critically evaluate the standard-setting inferences that can be drawn from value relevance research studies that are motivated by standard setting. Our evaluation concentrates on the theories of accounting‚ standard setting and valuation that underlie those inferences. Unless those underlying theories are descriptive of accounting‚ standard setting and valuation‚ the value-relevance literature’s reported associations between accounting numbers and common equity valuations
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Introduction Exchange rates play a vital role in a county’s level of trade‚ which is critical to every free market economies in the world. Besides‚ exchange rates are source of profit in forex market. For this reasons they are among the most watched‚ analyzed and governmentally manipulated economic measures. Therefore‚ it would be interesting to explore the factors of exchange rate volatility. This paper examines possible relationship between EUR/AMD and GBP/AMD exchange rates. For analyzing relationship
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THREE DAYS FACULTY DEVELOPMENT PROGRAMME (FDP) ON ABOUT SOCIETY FOR MANAGEMENT LEARNING Society for Management Learning (SML) is a recognized student organization of Lovely Professional University which is established by a group of dynamic business management students and scholars with an aim to elevate the understanding of practical implementation of management education. This society is committed to provide innovative learning techniques for management professionals. ABOUT RESOURCE PERSON
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Regression Project Purpose: The objective of this assignment is to expose you to the problems involved in building a regression model. The assignment requires you to collect data‚ to build a reasonable model‚ and to submit a short report on your findings. Data: The data for this project is data your group collects. First‚ specify a variable you wish to predict or explain; this will be your dependent variable. Then‚ specify at least three variables that will serve as predictor
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[pic] GSM 5000 MANAGERIAL ECONOMICS Problem Based Learning Lecturer : Dr. WAN AZMAN SAINI WAN NGAH By: Khong Yeen Lai GM 04349 PROBLEM BASED LEARNING: GSM5000 (MANAGERIAL ECONOMICS) GROUP 1 No. 1 You have been appointed as a member of a consultation team who is working on this very important assignment for a soft drink company. The main task is to evaluate
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University of Essex ESSEX BUSINESS SCHOOL Session 2009/2010 John Nankervis Email: jcnank@essex.ac.uk Carlo Rosa Email: crosa@essex.ac.uk BE953 (Empirical Methods in Finance) ASSESSED COURSEWORK The assessment for BE953 is by this coursework and a Final Examination. This piece of coursework is worth 50% of the overall assessment of BE953. The requirements for this coursework are as follows: • The coursework consists of data manipulation‚ analysis and interpretation. Although
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Regression Analysis for Strike with Damage Reported and Wildlife Strike II. ABSTRACT A wildlife strike into aircraft engines at takeoff and/or landing causes highly significant outcomes. The Federal Aviation Administration released Advisory Circular (FAA‚ AC150/5200-32B‚ 2013) to address importance of the reporting and encourage airline operators to report wildlife strike damage. The FAA conducted a study of wildlife strike reporting systems in mid 1990s and used a statistical analysis
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Three Month Treasury Bills and The Variables That Affect the Rates Abstract This paper attempts to create two models that can predict fluctuations in three-month US Treasury Bill yields. Using both simple and multiple regression analysis‚ we analyze the independent variables traditionally associated with risk free U.S. money market interest rates including the Consumer Price Index‚ the Industrial Production Index‚ and the Unemployment rate over two periods‚ July 1990-March 2001 and March 2001-December
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Regression with Time Series Data Week 10 Main features of Time series Data Observations have temporal ordering Variables may have serial correlation‚ trends and seasonality Time series data are not a random sample because the observations in time series are collected from the same objects at different points in time For time series data‚ because MLR2 does not hold‚ the inference tools are valid under a set of strong assumptions (TS1-6) for finite samples While TS3-6 are often too restrictive
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