EduRN: Economics Education (ERN) (Topic)最新文献

{"title":"Risk and Volatility: Q&A with Prof. Korok Ray","authors":"Brandes Institute","doi":"10.2139/ssrn.2987950","DOIUrl":"https://doi.org/10.2139/ssrn.2987950","url":null,"abstract":"Professor Korok Ray won the 2014 Brandes Institute Prize, awarded to an academic for compelling research in the fields of value investing and/or behavioral finance. Ray's winning entry will be published in The Journal of Investing. Here, Ray shares his insights in an exclusive discussion with the Brandes Institute Advisory Board.","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129600671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bayesian Examines the Lady Tasting Tea","authors":"P. E. Pfeifer","doi":"10.2139/ssrn.2975137","DOIUrl":"https://doi.org/10.2139/ssrn.2975137","url":null,"abstract":"This technical note accompanies the case/class on “The Lady Tasting Tea” (LTT). It describes how a Bayesian would update his or her prior probability for the probability the LTT can correctly distinguish cups of tea based on whether the milk was added first or last. This long-form note describes both a discrete model (LTT has p of 0.5 or 0.8) and a more complicated continuous model (p is beta distributed). The abridged note (UVA-QA-0768) describes only the discrete model. The case/class itself provides a very useful analogy with which students can explore the elements of statistical inference. \u0000Excerpt \u0000UVA-QA-0769 \u0000Jun. 13, 2011 \u0000A Bayesian Examines the Lady Tasting Tea \u0000Before I describe what Bayesian statistics can add to the discussion of the lady tasting tea (LTT), let me remind you where the classical statisticians left us. They used the binomial distribution to calculate the probability distribution of the number the LTT gets correct (in 10 trials) under two scenarios. The first scenario, called the null hypothesis, is that she is guessing. Guessing would mean P, the probability that she correctly identifies which of two cups has had milk poured into it first and which had tea in it first, is 0.5. The second scenario, called the alternative hypothesis, is that she is skilled. To keep things from getting too complicated, we assume that skilled means P = 0.8 for each trial. \u0000The resulting probability distributions are given in Table 1. With these probabilities, the classical statistician can make probability statements about what will happen undereither scenario. \u0000Table 1. Probability distributions for number correct in 10 trials. \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121086870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Twenty Questions for Every M&A: Improving Postmerger Integration Performance","authors":"A. Harvey","doi":"10.2139/ssrn.2975230","DOIUrl":"https://doi.org/10.2139/ssrn.2975230","url":null,"abstract":"This note is used in Darden's Postmerger Integration elective. The authors present a guide to help managers prepare for integration challenges and allocate integration resources more efficiently. Although simple at first glance, addressing 20 yes-or-no questions can lead to fruitful in-depth conversations that provide a sound foundation for successful PMI planning and execution. By answering these questions in open dialogue, PMI managers and senior executives will expose the potential weaknesses in an upcoming merger and highlight the arenas in which detailed planning is not only warranted but fundamental. \u0000Excerpt \u0000UVA-S-0226 \u0000Sept. 5, 2013 \u0000Twenty questions for every m&A: \u0000IMPROVING POSTMERGER INTEGRATION PERFORMANCE \u0000It is clear from the numbers that mergers and acquisitions (M&A) are difficult. By one estimate, about one-half fail to create shareholder value and around one-quarter actually destroy it. Yet despite this dismal track record, a 2011 McKinsey survey of senior executives noted that a majority of respondents still believe M&A remains necessary for growth. Much of the difficulty around acquisitions surely arises from the fact that every M&A is different, and most require a tailored, rigorous integration process to be successful. To price a deal right and successfully integrate the acquired business requires understanding what factors will make a given acquisition difficult and what resources the acquirer will need to tackle them. As the results show, many companies fail to do this successfully. \u0000Unfortunately, many of the firms that are considering M&A appear unprepared or inexperienced. In fact, a majority of the survey respondents noted that they do less than one acquisition a year, while just about one-half do not believe they have the required people or organizational resources to meet their M&A aspirations and only about one-third have dedicated integration teams. Thus it is not surprising that, since these integrations can require complex resource allocation decisions around how many employees, which specific employees, and what resources should be dedicated to the integration process, many fail to create value. \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132600294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Segmenting Clinton and Obama Voters","authors":"K. C. Lichtendahl, Rohit Gupta","doi":"10.2139/ssrn.2975172","DOIUrl":"https://doi.org/10.2139/ssrn.2975172","url":null,"abstract":"The purpose of this case is to introduce data visualization, advanced regression techniques, and supervised learning. Students are asked to visualize data geographically and in scatterplots. They will use stepwise regression and regression trees to select a predictive model for forecasting data in a holdout sample. In a forecasting competition, they will submit their models to be tested for accuracy. Supervised learning techniques—such as training, validation, and testing—are introduced. Regression trees serve as both predictive and graphical tools for communicating insights from data analysis to a decision maker. \u0000Excerpt \u0000UVA-QA-0807 \u0000Rev. Sept. 21, 2017 \u0000SEGMENTING CLINTON AND OBAMA VOTERS \u0000It was February 19, 2008. One week earlier, Barack Obama had taken the lead in the delegate count during the Democratic Party's presidential primaries, the winner of which would face the Republican Party's nominee in the general election to become the next president of the United States (POTUS). \u0000On that day in February, Hillary Clinton, Obama's primary opponent, began running ads in Ohio aimed at middle-class, blue-collar voters. One ad, “Night Shift,” closed showing Clinton at her desk: “She understands. She's worked the night shift, too.” But had Clinton ever worked the night shift? Her spokesperson said it was a “rhetorical reference” to working late nights as a lawyer, First Lady, and senator. \u0000Clinton was not alone in her awkward appeals to voters in key demographics. Months earlier at a campaign stop in Iowa, Obama noted that while produce prices had risen in grocery stores, farmers had not benefited from increases in crop prices: “Anybody gone into Whole Foods lately and see what they charge for arugula? I mean, they're charging a lot of money for this stuff.” At the time, there wasn't a single Whole Foods in the state of Iowa. \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132901066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managing Strategic Growth at Sjoland & Thyselius Ab","authors":"S. Schriber, Gerry Yemen","doi":"10.2139/ssrn.2975216","DOIUrl":"https://doi.org/10.2139/ssrn.2975216","url":null,"abstract":"Suitable for MBA, EMBA, and GEMBA courses, this case describes the organization and structure of a small European firm providing technical solutions to the defense industry. It combines crucial issues from strategic management and organization and management. The firm was founded by Magnus Sjoland and Rune Thyselius in Stockholm, Sweden, mainly working in the Swedish defense industry but also serving civilian customers. Having received the first large international order, the firm now stood to market itself on a broader international market. An open question is what resources the firm requires to compete in a global arena that differs in many ways from its well-known Swedish defense industry. At the same time, the firm structure demands too much of the owner managers leaving them unable to offer sufficient support for each division to prosper. The case offers unique possibilities to discuss the complex interaction of market forces, the control and management of valuable resources, and organization, in particular its structure and culture. \u0000Excerpt \u0000UVA-S-0189 \u0000Rev. Sept. 19, 2011 \u0000MANAGING STRATEGIC GROWTH AT SJOLAND & THYSELIUS AB \u0000It seemed extraordinary that, in 21 years, Rune Thyselius, chair and cofounder of Sjoland & Thyselius AB (S&T), and his partner, CEO Magnus Sjoland, had grown their business from a two-person programming firm to an important Swedish defense enterprise with 160 employees. Based in Stockholm, S&T offered a range of services, from management consulting, military training systems, construction engineering, and communication technologies to owning and running Scandinavia's only wind tunnel. Some reaching that level of success might have been ready to slow down and mull over an exit strategy, but Sjoland and Thyselius were looking to grow. \u0000Their first large-scale international project was well under way in the United Arab Emirates (UAE), and other opportunities in the international defense arena were possible. But was the firm ready for an international expansion? What internal actions would be necessary to create an organizational structure capable of supporting successful globalization? Should it continue to seek business in the UAE or target other markets? What organizational structure and which capabilities would be required to expand globally? \u0000The Early Years \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131330459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foundations of Welfare Economics and Product Market Applications","authors":"D. McFadden","doi":"10.3386/W23535","DOIUrl":"https://doi.org/10.3386/W23535","url":null,"abstract":"A common problem in applied economics is to determine the impact on consumers of changes in prices and attributes of marketed products as a consequence of policy changes. Examples are prospective regulation of product safety and reliability, or retrospective compensation for harm from defective products or misrepresentation of product features. This paper reexamines the foundations of welfare analysis for these applications. We consider discrete product choice, and develop practical formulas that apply when discrete product demands are characterized by mixed multinomial logit models and policy changes affect hedonic attributes of products in addition to price. We show that for applications that are retrospective, or are prospective but compensating transfers are hypothetical rather than fulfilled, a Market Compensating Equivalent measure that updates Marshallian consumer surplus is more appropriate than Hicksian compensating or equivalent variations. We identify the welfare questions that can be answered in the presence of partial observability on the preferences of individual consumers. We examine the welfare calculus when the experienced-utility of consumers differs from the decision-utility that determines market demands, as the result of resolution of contingencies regarding attributes of products and interactions with consumer needs, or as the result of inconsistencies in tastes and incomplete optimizing behavior. We conclude with an illustrative application that calculates the welfare impacts of unauthorized sharing of consumer information by video streaming services.","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126602760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Star Appliance Company (a)","authors":"D. Harrington","doi":"10.2139/ssrn.2974331","DOIUrl":"https://doi.org/10.2139/ssrn.2974331","url":null,"abstract":"An introduction to estimating the cost of capital, this case provides sufficient data for using a variety of methods for estimating the cost of equity, including the capital-asset-pricing model, and allows students to use their cost of capital in analyzing several investment projects. See also the B case (UVA-F-0684). \u0000Excerpt \u0000UVA-F-0421 \u0000STAR APPLIANCE COMPANY (A) \u0000Arthur Foster, the financial vice president of Star Appliance Company, thought that the opportunity had finally presented itself. Since joining the company in early 1978, he had been concerned about the hurdle rate used in the capital allocation process. He had not wanted to create a controversy immediately after accepting his position, but now in early October 1979, with the company considering a move into new products, he thought that the time had come to discuss the company's cost of capital. \u0000History of Star Appliance Company \u0000Star Appliance was founded in 1922 by Ken McDonald to manufacture electric stoves and ovens. During the prosperous 1920s, the demand for electric stoves and ovens as replacements for wood- and coal-burning stoves increased, and Star became a respected brand name and the market leader. Capitalizing on this success and the burgeoning equity market during the 1920s, McDonald financed the rapid growth of the company through the sale of common stock. This move proved to be farsighted. The company was able to enter the Depression with a debt-free balance sheet. Many firms, plagued with dwindling sales and poor or nonexistent profits had defaulted on their debts and were forced into bankruptcy and eventually out of business. Star suffered much during the Depression, but was able to survive by significantly reducing its operations and concentrating its sales efforts on the least affected part of the market, the premium end. As a result, Star remained alive and viable, emerging at the end of World War II with a smaller base of operations, a strong balance sheet, and a well-established reputation in the marketplace. \u0000In the ensuing three decades, the company grew and prospered. Star continued to concentrate on the premium market and over the years expanded its product line. Continuing its focus on kitchen appliances, Star first added gas ranges to its products, followed by a line of refrigerators. Microwave ovens were the company's latest product. The company's marketing program emphasized the sale of new appliances as replacements for older models, rather than targeting the market for installations in newly constructed dwellings. This strategy provided some protection from the vicissitudes of the highly cyclical housing industry. \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114533412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ben & Jerry's Homemade: The Unilever Scoop","authors":"Gerry Yemen, G. Allayannis, Michael J. Schill","doi":"10.2139/ssrn.2974480","DOIUrl":"https://doi.org/10.2139/ssrn.2974480","url":null,"abstract":"A follow up for Ben & Jerry's Homemade (UVA-F-1364), this case is suitable for MBA, EMBA, and GEMBA programs, and could work as a stand-alone undergraduate introduction to corporate finance and M&A or an introductory strategy class on M&A or post-merger integration. Did the Unilever/Ben & Jerry's merger yield both firms' fundamental objectives? What did the market think? What did each get from the deal? What can students tell about where future value will lay? The case allows students to discuss post-merger integration issues and what makes for a successful merger. The case requires little or no calculations. \u0000Excerpt \u0000UVA-F-1656 \u0000Aug. 18, 2011 \u0000BEN & JERRY'S HOMEMADE: THE UNILEVER SCOOP \u0000Four offers were on the table to purchase Ben & Jerry's Homemade (Ben & Jerry's) in early 2000; in the end, Unilever's deal was by far the most attractive. And now, 10 years after becoming a subsidiary of the Dutch global consumer product company, much had changed at Ben & Jerry's—and much had remained the same. \u0000By the time the purchase was announced in South Burlington, Vermont, on April 12, 2000, Ben & Jerry's pre-deal stock price of $ 21 had increased substantially, to just shy of $ 35, and the company had $ 237 million in sales and $ 3.4 million in earnings. Unilever had increased its earlier tender offer of $ 36 to $ 43.60 per share or $ 326 million total, to be paid in cash (see Exhibit 1 for stock price charts). Both Unilever and Ben & Jerry's hoped to benefit from the acquisition. \u0000The Unilever muscle offered Ben & Jerry's an opportunity to scale up and enter several new markets internationally—something it had not been able to do previously. Unilever was one of the largest global firms in the world operating in 88 countries, employing 255,000 worldwide, and earning sales over $ 45 billion in 1999. Within the US, the company had 66 offices, manufacturing operations in 23 states, 22,000 people, and over $ 8 billion in sales. With increased access to capital and resources, Ben & Jerry's would have the potential to dramatically increase the size and social impact of its brand. \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121249618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Measurement with Factor Models","authors":"R. Evans","doi":"10.2139/ssrn.2974492","DOIUrl":"https://doi.org/10.2139/ssrn.2974492","url":null,"abstract":"Identifying an appropriate benchmark is an essential step in assessing a manager's performance. In the prospectus or fund advertising materials, a benchmark for the fund is typically identified, and the performance of the fund relative to that benchmark is given. The issue of concern is whether or not the benchmark provided has a similar risk profile to the fund. \u0000 \u0000Excerpt \u0000 \u0000UVA-F-1673 \u0000 \u0000Rev. Nov. 27, 2012 \u0000 \u0000PERFORMANCE MEASUREMENT WITH FACTOR MODELS \u0000 \u0000Identifying an appropriate benchmark is an essential step in assessing a manager's performance. In the prospectus or fund advertising materials, a benchmark for the fund is typically identified, and the performance of the fund relative to that benchmark is given. The issue of concern is whether or not the benchmark provided has a similar risk profile to the fund. Factor models, such as the Capital Asset Pricing Model (CAPM), generate a benchmark return for each fund based on its beta or systematic risk. Specifically, the expected return for a fund according to the CAPM (which I refer to below as RFundCAPMBenchmark) is given by Equation 1: \u0000 \u0000RFundCAPMBenchmark Rrisk-free Fund(RMKT – Rrisk-free). (1) \u0000 \u0000The beta of the fund is estimated by calculating the slope of the regression line of the excess return of the fund (RFund – Rrisk-free) on the excess return of the market (RMKT – Rrisk-free). Using this estimate of beta and the average returns of the market portfolio and the risk-free asset, we can compute the expected return of the fund, given the systematic risk taken by the manager. The value added by the manager or alpha is the difference between the total return on the fund for the period (RFund) and the benchmark return for the fund as determined by the CAPM formula (RFundCAPMBenchmark) given in Equation 2: \u0000 \u0000. . .","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133881217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is Something Really Wrong with Macroeconomics?","authors":"R. Reis","doi":"10.1093/OXREP/GRX053","DOIUrl":"https://doi.org/10.1093/OXREP/GRX053","url":null,"abstract":"While there is much that is wrong with macroeconomics today, most critiques of the state of macroeconomics are off target. Current macroeconomic research is not mindless DSGE modeling filled with ridiculous assumptions and oblivious of data. Rather, young macroeconomists are doing vibrant, varied, and exciting work, getting jobs, and being published. Macroeconomics informs economic policy only moderately and not more nor all that differently than other fields in economics. Monetary policy has benefitted significantly from this advice in keeping inflation under control and preventing a new Great Depression. Macroeconomic forecasts perform poorly in absolute terms and given the size of the challenge probably always will. But relative to the level of aggregation, the time horizon, and the amount of funding, they are not so obviously worst than those in other fields. What is most wrong with macroeconomics today is perhaps that there is too little discussion of which models to teach and too little investment in graduate-level textbooks.","PeriodicalId":409545,"journal":{"name":"EduRN: Economics Education (ERN) (Topic)","volume":"18 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116786325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}