...2029-4433 (Online) Journal homepage: http://www.tandfonline.com/loi/tbem20 Evaluation of some business macro environment forecasting methods Vulfs Kozlinskis & Kristine Guseva To cite this article: Vulfs Kozlinskis & Kristine Guseva (2006) Evaluation of some business macro environment forecasting methods, Journal of Business Economics and Management, 7:3, 111-117 To link to this article: http://dx.doi.org/10.1080/16111699.2006.9636131 Published online: 14 Oct 2010. Submit your article to this journal Article views: 1769 View related articles Citing articles: 1 View citing articles Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=tbem20 Download by: [86.20.58.206] Date: 10 November 2015, At: 14:42 Journal of Business Economics and Management 2006, Vol VII, No 3, 111117 ISSN 1611-1699 EVALUATION OF SOME BUSINESS MACRO ENVIRONMENT FORECASTING METHODS Vulfs Kozlinskis1, Kristine Guseva2 Riga International School of Economics and Business Administration (RISEBA), Meza iela 1, k. 2, LV-1048 Riga, Latvia E-mail: 1Vulfs@rsebaa.lv, 2 kris@rsebaa.lv Downloaded by [86.20.58.206] at 14:42 10 November 2015 Received 06 03 2006; accepted 28 04 2006 Abstract. Latest studies in the field of business macro environment (BME) assessment and forecasting have been undertaken and successfully implemented by the World Bank (2003-2004). Considerable contribution to the field has...
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... & Forecasting Copyright © 2014, 2011, and 2008 Pearson Education, Inc. 14-2 Content 1 2 3 4 5 6 Descriptive Analysis: Index Numbers Descriptive Analysis: Exponential Smoothing Time Series Components Forecasting: Exponential Smoothing Forecasting Trends: Holt’s Method Measuring Forecast Accuracy: MAD and RMSE Copyright © 2014, 2011, and 2008 Pearson Education, Inc. 14-3 Content 7 8 9 Forecasting Trends: Simple Linear Regression Seasonal Regression Models Autocorrelation and the DurbinWatson Test Copyright © 2014, 2011, and 2008 Pearson Education, Inc. 14-4 Learning Objectives • Focus on methods for analyzing data generated by a process over time (i.e., time series data). Present descriptive methods for characterizing time series data. Present inferential methods for forecasting future values of time series data. Copyright © 2014, 2011, and 2008 Pearson Education, Inc. • • 14-5 Time Series • • • • Data generated by processes over time Describe and predict output of processes Descriptive analysis – Understanding patterns Inferential analysis – Forecast future values Copyright © 2014, 2011, and 2008 Pearson Education, Inc. 14-6 14.1 Descriptive Analysis: Index Numbers Copyright © 2014, 2011, and 2008 Pearson Education, Inc. 14-7 Index Number • • • Measures change over time relative to a specific base period Price Index measures changes in price – e.g. Consumer Price Index (CPI) Quantity Index measures...
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...Forecasting Methods Assignment University of Phoenix MGT 554: Operations Management Steven Williams August 28, 2006 Introduction Forecasting can be defined as Estimating or predicting future events or conditions. Forecasts may be long-term or short-term. The techniques used may be quantitative (often making sue of computers) or qualitative. Quantitative forecasting models may be classified into (a) causal models in which independent variables are used to forecast dependent variables, and (b) time series models, which produce forecasts by extrapolating the historical values of the variables of interest by, e.g., moving averages. Seasonal Model Seasonality is a pattern that repeats for each period. For example annual seasonal pattern has a cycle that is 12 periods long, if the periods are months, or 4 periods long if the periods are quarters. The seasonal index is required to be found for each month, or other periods, such as quarter, week depending on the data availability (Hossein, 1994-2006). Seasonal Index: Seasonal index represents the extent of seasonal influence for a particular segment of the year. The calculation involves a comparison of the expected values of that period to the grand mean. A seasonal index is how much the average for that particular period tends to be above (or below) the grand average. Therefore, to get an accurate estimate for the seasonal index, compute the average of the first period of the cycle, and the second period...
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...Running Head: ECONOMIC FORECASTING PAPER Team B Weekly Reflection - Economic Forecasting Paper Chelsea Heyd, Andrea Zugelder, Roberto Foster, Pam Pudans, Kelly Day August, 26th 2014 ECO/372 BARNHILL Team B Weekly Reflection - Economic Forecasting Paper The following includes a list of resources that could be used to gather historical economic data as well as economic forecast data. The resources included are general enough to be applicable to a broad range of potential research project types. However, the data that is accessible in any of the following resources is specific enough to not only represent correctly quantifiable theories with facts, but also to display facts relevant to a variety of potential historical economic research as well as economic forecasting. Chicago Fed National Activity Index (CFNAI) Monthly, this resource measures overall economic activity and inflation based on production and income. Also, employment, unemployment, and hours worked is tracked and displayed using this web resource. Several other unique, key data that can be found her includes personal consumption and housing; and sales, orders, and inventories. The data shown in this resource is valuable for predicting inflation, as well as gauging current and future economic activity in the US on a Macroeconomic level. FDIC State Profiles These state profiles have recently been updated as a quarterly data sheet that summarizes the banking and economic conditions of each...
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...Forecasting with Indices Forecasting is a tool that a company can use to predict trends or patterns based on the data available from previous years, quarters or periods. Forecasting can assist a company with a wealth of information, such as where cuts need to be made, where increases need to be made. Forecasting can even aid a company with what product to carry or discontinue and when would be a good time for a sale. Calculating Averages Taking the monthly sales for the last four years of Honda’s sales, the author entered this information into Excel, and formulated this chart: | Year | Year | Year | Year | average by month | Month | 1 | 2 | 3 | 4 | monthly index | 1 | 98,511 | 71,031 | 67,479 | 76,269 | 78,323 | 2 | 115,397 | 71,575 | 80,671 | 98,059 | 91,426 | 3 | 138,734 | 88,379 | 108,262 | 133,650 | 117,256 | 4 | 135,180 | 101,129 | 113,697 | 124,799 | 118,701 | 5 | 167,997 | 98,344 | 117,173 | 90,773 | 118,572 | 6 | 142,539 | 100,420 | 106,627 | 83,892 | 108,370 | 7 | 138,744 | 114,690 | 112,437 | 80,502 | 111,593 | 8 | 146,855 | 161,439 | 108,729 | 82,321 | 124,836 | 9 | 96,626 | 77,229 | 97,361 | 89,532 | 90,187 | 10 | 85,864 | 85,502 | 98,811 | 98,333 | 92,128 | 11 | 76,233...
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...HR Plan-09s HR Demand: Demand Forecasting Techniques I. Index/Trend Analysis II. The Delphi Technique III. Moving Average Method IV. Regression Analysis Method I. Index/Trend Analysis Examining the relationship over time between an operational business index, such as level of sales, and the demand for labour (as reflected by the number of employees in the workforce) is a relatively straightforward quantitative demand forecasting technique commonly employed by many organizations (see the following Table) Table: Index/Trend Analysis |Year |Sales |Number of Employees |Index | | |(Tk thousands) | |(Sales [Tk thousands] per Employee) | |2003 |2800 |155 |18.06 | |2004 |3050 |171 |17.83 | |2005 |3195 |166 |19.25 | |2006 |3300 |177 |18.64 | |2007 |3500 |188 |18.64 ...
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...Forecasting with Indices Christopher L Kearney University of Phoenix QRB/501 Quantitative Reasoning for Business Maryam Boluri May 2, 2011 Forecasting with Indices This writer will begin by defining forecast and index while detailing the importance of both as they relate to the makeup of any company. This type of data can be financial or non-financial depending on what the company offers. Forecasting is a method used by companies to predict current and future trends. Many companies have realized this to be the backbone of the company because it predicts whether or not a company will break even and if a company does not break even decided whether the company will be up and running the following year. An index is a point of reference concerning numbers with common points. Indices are used to observe historical and short-term comparisons with percentages change commonly used. This week’s lesson entailed obtaining the Summer Historical Inventory Data from the materials area in the week two forum and converting the information into an index. The time series information is to be used to forecast the inventory needed for the upcoming year. To give a company a better view of making decision a month-to-month forecast is best because more information can be obtained over a shorter period. The Summer Historical Data obtained from University of Phoenix Material was converted into an index using Microsoft excel software. The data showed typical demand for summer highs using...
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...The analysis done clearly indicates that the maximum sale is achieved between the month of June and September. The graph shows an upward trend indicating the regular increase in sales. We also calculated Mean Absolute percentage Variance to calculate our accuracy. It came out to be 2.5 which suggest our accuracy is 97.5% which is clearly not bad but to stay that way, we will have to monitor the forecasting every quarterly if not monthly because of the cost involved in it. Necessary changes should be made after forecasting it because strategic implementation is more necessary. Otherwise, forecasting will be of no use. We have also provided some recommendations for managing their capacity to equip themselves better in the high sales month and to get rid of the extra cost in the low sales month providing the cost effectiveness. TABLE OF CONTENTS Introduction----------------------------------------------------------------------------------------------------4 Sales Trend-----------------------------------------------------------------------------------------------------4 Seasonal Index-------------------------------------------------------------------------------------------------5 Sales Forecast--------------------------------------------------------------------------------------------------6...
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...QRB/501 – Quantitative Reasoning for Business University of Phoenix Inventory Proposal This proposal is for a solution for an inventory problem within an organization. The details of the organization’s business operations are established and the problem identified so a potential solution may be formulated and proposed. The expected benefits to the organization are also examined as the motivation for implementation. Additionally, an inventory index is used to compare and contrast historical trends leading to the inventory problem and supporting evidence is presented through a histogram and slope-intercept calculations. Organization Vertical Entertainment (VE) is a fireworks wholesaler headquartered in Austin, Texas. VE has been in business since 2005 and provides fireworks products through business-to-business and business-to-consumer channels. The organization’s key segments are the small-box retailers and fireworks display companies. The small-box retailers account for increased volume during the summer months (e.g. 4th of July) whereas the fireworks display companies purchase goods year-round. In recent years VE has expanded to direct sales via the company website. Inventory Problem VE purchases all firework inventories directly from China and they arrive in roughly 12 weeks. Product backorder usually result in lost sales because most events are time specific. The main inventory issue...
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...a p p e n d i x C DEMAND FORECASTING IN MARKETING * When you finish this appendix you should • Understand the principles of forecasting. • Know the differences between Time Series and Regression Analyses. • Understand how expert opinion, sales forces and consumer opinions can all contribute to better forecasts. * by Beverley Thompson, The University of Western Sydney, Nepean Demand Forecasting in Mar keting w 689 An important part of the marketing planning process is the setting of goals that are realistic and achievable, given a particular marketing environment and level of marketing commitment. In marketing, such goals are usually based on market share objectives and sales targets, both of which require accurate forecasts of total market size, market size of target segments and likely market share within a targeted segment. W H AT A R E W E F O R E C A S T I N G ? Accurate forecasting requires a clear definition of the market in question. Markets may be differentiated on the basis of the following variables. GEOGRAPHY A market may be defined at world, country, state, region, sales territory, town, store or customer level. When formulating a forecast or other marketing plans, the geographical dimension must be clearly indicated. Planning Coca Cola consumption for the year 2000 Sydney Olympics for example, will necessitate the forecasting of increased consumption for the Sydney sales region, but not necessarily for Brisbane...
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...It doesn’t not allow project managers to know whether deviation from planned values is critical and require an immediate corrective actions or not. Traditional EVM does not reflect the actual schedule performance at the project last third since at the project end, schedule performance index will reach 1 and all budget will be earned. This is affecting the creditability of schedule prediction and expected cost at completion. In this regard, (Lipke, 2005) has proposed an enhancement to the traditional EVM by using the concept of Earned Schedule (ES). The Earned Schedule (ES) had improved the reliability of the indicators for the whole project including early and late start despite EVM which is limited to early finish only. ES focuses on cost and schedule using EVM while EVM is focused on cost only. ES is increasing the forecasting reliability as the project progresses to the end. Testing earned schedule forecasting reliability on real and simulated projects shows that applying earned schedule (ES) has significantly increased the outcome reliability (Lipke,...
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...Inventory Proposal: Analysis of University Of Phoenix Demand for Units QRB501 Inventory Proposal University of Phoenix is a for-profit university initiated in 1976 by John Sperling (Kinser, 2006). The university originated in the Phoenix metropolitan area and started with only eight students (Kinser, 2006). Sperling wrote about the origin of University of Phoenix and refers to it as “Rebel with a Cause” (Kinser, 2006, para. 2). Sperling experienced much opposition in getting UOPX in operation to help underserved and hard working adults further their education. Thanks to his determination and confrontational side, Sperling is 88 and can see UOPX having a net worth of $9 billion (Kinser, 2006). University of Phoenix is top on the list of for-profit universities. They enroll more than 230,000 students and have 170 throughout the United States (Kinser, 2006). It is apparent to past critics that universities who provide opportunities for working adults are growing at a rapid rate. More students are leaning to online schools and universities to advance with higher degrees. One thing plaguing the United States is the economy. The cost of tuition is steadily increasing, making it more difficult for students to afford education without the help of scholarships, grants, and student loans. It is said that for-profit universities depend heavily on federally funded students to stay afloat financially (Field, 2011). There are reports and suits filed from past instructors...
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...Discussion Questions: 1,7, and 15 1: (a) What is forecasting? Why is it so important in the management of business firms and other enterprises? (b) What are the different types of forecasting? (c) How can the firm determine the most suitable forecasting method to use? a) Forecasting is used to try and predict the economic activity of a firm’s future. It aims to reduce risk/uncertainty that is faced in the short-term operational decision making. It is also used to plan for the firm’s long-term growth. Forecasting helps make decisions by using macroforecasts of the general economic activity as inputs for their microforecasts of the industry’s and firm’s demand and sales. Forecasting helps decide a firm’s marketing strategy, production needs, sales forecast, and helps predict financial needs such as cash flow, profits, and outside financing. Furthermore, it helps make personal based decisions, as well as assist for the long-term future of the firm (Salvatore, 2012). b) Forcasting types range from expensive to inexpensive, as well as simple to complex. Forecasting techniques can be qualitative, and others can be quantitative. Salvatore focuses on qualitative forecasts. These forecasts include: time-series, smoothing techniques (moving averages), barometric forecasts with leading indicators, econometric forecasts, and input-output forecasts. c) A firm determines the most suitable forecasting method to use by using the following criterion: ...
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...Forecasting and Indices Forecasting is a process in which statements or conclusions are made regarding the outcome of events that have not yet happened. Forecasting is predicting what the could look like. There are many examples of forecasting. Estimating or predicting can be referred to as formal statistical methods that employ time series, cross-sectional or longitudinal data. Forecasting can be use to estimate a wide variety of issues, weather related events, the use of resources, sales, profit or loss and even staffing needs for a particular project. Coupling these findings with good planning can give a company a good indication of what the future should look like. Forecasting can use many different methods. Evaluating your objectives and conditions relevant to the individual situations can help in choosing the correct method to use. Another option is to use several methods and compare or combine the results, as many times, there is no one “best” method. “The forecast error is the difference between the actual value and the forecast value for the corresponding period. where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t. Measures of aggregate error: Mean absolute error (MAE) Mean Absolute Percentage Error (MAPE) Mean Absolute Deviation (MAD) Percent Mean Absolute Deviation (PMAD) Mean squared error (MSE) Root Mean squared error (RMSE) Forecast skill (SS) Average of Errors (E)...
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...TOPIC 1. FUNDAMENTALS OF ECONOMIC FORECASTING TOPIC I TOPIC I. FUNDAMENTALS OF ECONOMIC FORECASTING Contents 1. Meaning of forecasting 2. Features, importance and limitations of forecasting 3. Forecast types 1. Meaning of forecasting Forecast is a likely, scientifically well-grounded opinion about the possible state of the events, objects or processes in the future. Forecasting is a process of making statements about events whose actual outcomes (typically) have not yet been observed. Forecasting is a process of predicting or estimating the future based on past and present data. Economic Forecasting is a process of making forecasts based on analysis of past trends and regularities of the economic processes. Economic forecasts can be carried out at a high level of aggregation – for example for GDP, inflation, unemployment or the fiscal deficit – or at a more disaggregated level, for specific sectors of the economy or even specific companies. Economic forecasting provides information about the potential future events and their consequences for the organization. It may not reduce the complications and uncertainty of the future. However, it increases the confidence of the management to make important decisions. Economic forecasting includes the following steps: 1. Identifying items to be forecast. The items of socio-economic forecasting are the economic processes (for example, inflation, demand, supply), any indicator describing the company activity (for example...
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