Effect of German Automobile Industry on Economy - Essay Example

The German Automobile Industry and the affect it has on the German Economy, Stock Utility Analysis This paper uses long-run real price and dividends series to investigate for the German stock market the questions asked of the U.S. market by Shiller (1989). It tries to determine in what periods and to what degree the German stock market has also possessed "excess volatility" in the past century in relation to the car industry. It finds no evidence of excess volatility in the pre-World War I German stock market indices in the car industry. By contrast, there is some evidence of excess volatility in the post-World War II German stock market. Introduction: The automobile industry plays a significant role in the German economy; every fifth job is directly or indirectly connected to it. This implies that Germany's economic strength is being impacted and influenced by the automobile industry to a great extent - making it one of the most dominating sectors. The value system in the German car industry can be broken down into four major players; component suppliers, car producers, dealers or the point of sale, and buyers. These players are all affected by any turbulence in the car industry. As a result they all contribute, to various extents, to the attempts of structural change taking place in the industry. As Muller and Reuss have argued perhaps what is most noticeable of the attempts at readjustments within the value system is the insecurity on the part of all players as to what the future direction of the industry will be. Background: Germany has a leading position in car manufacture worldwide, owing mainly to the fact that the focus was concentrated on high technology in order to be able to fulfill the increasing demands of the markets and to maintain the export power of German car manufacturers. The car industry, which represents a macroeconomic key industry for Germany, made a turnover of 202 billion EUR in 2001. 69% was attributable to manufacturers of motor vehicles and motors, a good 3% to the manufacturers of trailers, body work and containers; 28% to the car components and accessories industry. With this, the car industry made one-sixth of the total industrial turnover in Germany. With 121 billion EUR, the German car industry earned 60% of its sales in foreign countries. German car manufacturers and suppliers employ more than 1.5million people worldwide, more than half of them in Germany. Recently, domestic employment has been expanded; Since 1994, the number of jobs at home increased by122000.Despite economic weakness in 2002, employment in the car industry remained almost constant with 763 500 people. Owing to the assumption of additional value-added activities from the manufacturers, suppliers even employed additional staff. The German car industry employs more than 12.8% of the working population of the whole German industry. At the same time, it raises one third of the R&D expenditure of the German economy and one-fifth of the investments. During the last five years, 49 billion EUR were invested in Germany; over this period of time, expenditure for R&D exceeded 65 billion Euros, and the R&D staff was increased significantly to more than 70,000 employees (VDA, 2003). Literature Review: Germany was one of the European countries that succumbed early to the fascination of Fordist production methods. German automakers made pilgrimages in the 1920s to the USA, seeking to discover the secrets of the economic future at the holy cities of capitalism, which of course included the Ford plants at Highland Park and River Rogue. Creating the preconditions for a new age in automobile production was a strong motive behind numerous efforts to concentrate car production capacity in Germany. After the postwar stabilization of the economy, the large German banks - above all the Deutsche Bank - toyed with the idea of consolidating the most important German car producers into a large automobile trust, able to meet the challenge of Ford; Daimler, Benz, Opel and BMW were still only medium sized companies. Daimler and Benz merged in 1924-6. But all further efforts in this direction were hampered by unfavorable economic circumstances, and they ended abruptly in spring 1929 when Adam Opel AG was sold to General Motors at a large profit. This effectively ended serious discussion of a German Auto Trust and intensified what was known as the creeping crisis of the German automobile industry. This paper examines "excess volatility" in the market indices of major car manufacturers in the German stock market, investigating for that market the issues examined by Robert Shiller (1981, 1986, 1989) for the U.S. stock market. It finds some evidence that post-World War II German stock index prices in the car industry have been too volatile (relative to nave estimates of fundamentals) to have been rational forecasts of the present value of future dividends. Alternatively, pre-World War I stock prices were not volatile enough (relative to nave estimates of fundamentals). In either case, the efficient markets hypothesis appears inconsistent with observed behavior in one or the other of the periods. The focus of this paper is on the divergence of market outcomes in the two periods, and the difficulty of reconciling both patterns simultaneously with the efficient markets hypothesis. This paper examines the volatility of prices relative to dividends in order to avoid most of the biases in estimated volatility ratios generated by Shiller's (1981) original tests. Thus normalized, the pre-World War I German stock market shows not excess but deficient volatility: the market price dividend ratio is surprisingly far down in the lower tail of the distribution under the null hypothesis that prices are rational forecasts of fundamentals. Throughout the pre-World War I era, the market average dividend yield fluctuates in a narrow band between four and a half and five and a percent. By contrast, the post-World War II stock market (and especially the post-Wirtschaftswunder market) shows some evidence of "excess" volatility. The evidence of excess volatility in post- World War II German data is weaker than but of the same order of magnitude as the evidence using U.S. post-World War II data. The behavior of the pre-World War I German stock market thus is in sharp contrast to the behavior of the post-World War II German stock market, and to the behavior of the U.S. stock market in either the pre-World War I or the post-World War II period. We speculate that the dominance of the German Grobanken in the securities industry in the years before World War I may be the cause of the exceptional behavior of the pre-World War I German market. German Data: Donner (1934) compiles and reports a monthly nominal share price index-with attached estimates of average yearly dividend yields for the companies included in his aggregate index-for the German stock market from January 1870 to December 1913. His index covers only twelve companies from 1870 to 1875. The number of companies covered reaches twenty-one in 1876 and is nearly sixty by 1890. Majority of the companies included in the reports belongs to the automobile industry as such Volkswagen, Ford, BMW, Mercedes and Audi. Especially in the years from 1890 on, the Donner index is a sample of Germany's largest companies, weighted toward those heavy industries in which Germany's companies were largest and its international comparative advantage greatest. We begin our study in 1876, when the number of companies in the index rises above twenty. Donner's index ends with the beginning of World War I. An official index-unfortunately without dividends attached-covers the period from 1914 up to the 1923-24 hyperinflations (Statistisches Reichsamt, 1922a, 1922b). A second official index covering three hundred corporations extends from 1924 to the middle of World War II, reporting both the stock index price and a dividend yield (Statistisches Reichsamt, 1928, 1929). We splice the first official Statistisches Reichsamt (National Bureau of Statistics) series onto Donner's in 1914 to track the course of the German stock market up to the hyperinflation. We splice the second Reichsamt index onto the first to provide information about the course of the German stock market between the hyperinflation and the middle of World War II. For the post-World War II period, the stock price series we use links four official portfolio index series constructed by the post-World War II Statistisches Bundesamt (Federal Bureau of Statistics).We link from each series to the next in the first year in which the following sequence becomes available (see Herrman, 1956; Spellerberg and Schneider, 1967; Silberman, 1974; Ltzel and Jung, 1984; Statistisches Bundesamt, 1985). For the later interwar and the post-World War II periods, the yield series used is the yield on all traded stocks. Thus the yield is calculated from a different and larger sample of corporations than are the price indices. Nevertheless, the post-World War II dividend series-calculated by multiplying price and yield-is a good estimate of the dividend corresponding to the index. The nominal price and dividend series are deflated by the German consumer price index endorsed by the Deutsche Bundesbank (1976). This index runs continuously, with one gap covering World War II and the post- war reconstruction period Excess Volatility and the German Stock Market Shiller's (1981, 1989) first key insight was that the level of the stock market is a forecast of the ex post perfect-foresight fundamental. An investor who buys and holds, and pays less than the ex post fundamental, receives a supernormal return. Arbitrage, therefore, pushes prices in an efficient market to be efficient forecasts of the perfect-foresight fundamental. Shiller's second key insight was to apply the principal that efficient forecasts are less volatile than the ex post realized values of the quantities being forecast. If a forecast is more volatile, a better forecast could be constructed easily: shrink the original forecast toward its ex ante unconditional mean, and the resulting improved forecast will have a smaller mean squared error. These two insights imply that if the efficient markets hypothesis holds then stock prices should be less volatile-relative to their ex ante unconditional means, a notion that needs to be made precise-than the realized track of the ex post perfect-foresight fundamental. Biases in Testing for Excess Volatility As Flavin (1985), Scott (1985), Kleidon (1986a and 1986b), Mankiw, Romer, and Shapiro (1985, 1991), and many others have argued, Shiller's (1981) original comparison of the variance of deter ended prices and of deter ended ex post perfect-foresight fundamentals are subject to biases. Especially in small samples, such tests may well find apparent excess volatility even if in fact the efficient markets hypothesis holds. It is easiest to understand the source of these biases by examining the trading strategies associated with tests of excess volatility and return predictability. Each test of market rationality is implicitly associated with a portfolio strategy. If prices are too volatile relative to trend, investors at the time could have made better forecasts of ex post fundamentals-and earned high profits-by taking as their forecast some linear combination of the market price and a time trend, and betting that returns would be low whenever the market price was above the trend. If returns are predictable from a variable like the price-dividend ratio (Scott, 1985), investors could have earned supernormal profits by buying when the ratio was low and selling when it was high. If investors could in fact have followed the trading strategy implicit in the tests of market efficiency-and did not-then the rejection of market efficiency is genuine. But under some conditions the implicit trading strategy could not have been followed because it required more information for its execution than investors at the time possessed. In such a case, the rejection of market efficiency may well be spurious: investors may well have taken advantage of all profit opportunities open to them, and given the information at their disposal prices may have been the best available forecasts of the present value of fundamentals. For example, suppose log dividends follow a random walk with drift: Where g is the long-run upward rate of drift of dividends, and et is an innovation, un forecast able before period t. With a constant discount rate r, the efficient markets log real stock price will be: (2) pt = -ln(r-g) + dt Suppose an ex post time trend p is fitted to the first and last observations, t=0 and t=T: (3) pt= p0+Tt (pT- p0) Calculate the covariance between the one-year realized return r*t1: (4) r*t1= r + et and the price relative to the ex post time trend (conditional on knowledge of the current price pt and of the current value pt of the ex post trend): (5) E{r*t1 (pt-pt) | pt-pt} = - {Tt} E {et+12 | pt-pt} Equation (5) shows that there are excess returns from buying when the price is low relative to the ex post trend, and selling when it is high. Such a strategy earns excess returns off of the correlation between the deviation of the price from the ex post trend and future innovations. The return predictability in equation (5) comes solely from the use of the realized values of future shocks-shocks dated later than t-in constructing the value pt of the time trend, and in assessing whether prices are relatively low or high. Without this use of information about the realizations of future shocks, there are no excess returns to be earned: returns are uncorrelated with the deviation of the price from an ex ante time trend p't constructed by extrapolating drift from the series starting point. (6) p't= p0+ tg (7) E{r*t1 (pt-p't)| pt, p't} = 0 In this example, a regression of returns on prices and an ex post time trend is indeed likely to find significant return predictability and excess volatility. But such a finding is spurious: it arises from an implicit assumption that rational investors had more information about future shocks than they in fact possessed future shocks. Normalizing by the Level of Dividends To compensate for such biases, Mankiw, Romer, and Shapiro (1985 and 1991) proposed an alternative benchmark for the calculation of excess volatility. They argued that it is plausible that past investors knew nave forecasts of perfect-foresight fundamentals made by assuming them to be a constant dividend multiple. Tests of excess volatility relative to this alternative nave-forecast benchmark that takes fundamentals to be a constant multiple of dividends assume less in terms of investors' knowledge of the parameters and outcomes of the dividend process. This paper uses such a nave constant dividend multiple forecast as the benchmark against which to evaluate the efficient markets hypothesis. It normalizes real prices and ex post fundamentals by the current level of dividends. The pre-World War I stock market does not appear excessively volatile to the eye: the volatility of prices relative to the benchmark of twenty times dividends is smaller than the volatility of ex post fundamentals. The post-World War II market does see a larger volatility for prices relative to the twenty times dividends benchmark than for ex post fundamentals after 1960. The decade before1960 sees both prices and ex post fundamentals very far from normal multiples of dividends. Conclusion: This paper has used German data to investigate issues similar to those that Shiller (1989) has investigated in his studies of the United States stock market. The German data give different answers. There is some evidence of excess volatility in the post-World War II German stock market. But there is no sign at all of excess volatility in the pre-World War I German stock market. Relative to a nave forecast benchmark that takes fundamental values to be a constant multiple of dividends, the pre-World War I German stock market stands in contrast to both the post-World War II German market, and to the American market in either the pre-World War I or the post-World War II period. The substantive results of this paper suggest two additional lines of thought. The first is that in a sense the absence of excess volatility in the German stock market before World War I strengthens Shiller's conclusions for the United States. It is harder to maintain that Shiller's findings of violations of market efficiency are due primarily to biases in test procedures or to inappropriate assumptions about the stochastic character of generating processes when the pre-World War I German stock market- presumably subject to the same biases in test procedures -exhibits no signs of excess volatility. 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