قیمت سهام ایالات متحده و شوک های واقعی عرضه و تقاضا

Demand and supply sources of output movement are distinguished and the effects of shocks on stock prices are analysed. The real economy has a more pronounced effect on the stock market than vice versa and the influence from the real economy to the stock market is less important than shocks that are peculiar to the market itself. Supply and demand shocks have a greater impact on stock prices than they do on real economy variables and the sensitivity of real stock prices to supply fluctuations has waned while the sensitivity of real stock prices to demand-driven output fluctuations has increased.

The interaction between the stock market and aggregate economic activity has been the subject of considerable interest in the past decade. The relationship has traditionally been one in which the economy affects the stock market, usually based on the common text-book model of share prices as the discounted present value of expected future dividends. In this framework, share prices are influenced both by output (via profits and dividends) and interest rates (via the rate at which future dividends are discounted). More recently, attention has also been focussed on effects in the opposite direction, that is, from the stock market to the economy, no doubt influenced by the strong stock market performance in the 1990s and the sharp “corrections” in 2001 following the long bull market. The extant literature has identified two principal channels of influence, the first from stock prices to consumption via a wealth effect and the second from stock prices to investment via cost of capital and other influences.1 The vector autoregressive (VAR) model has been a popular one for the analysis of the intertemporal relationships between macro variables and stock prices; it requires little by way of prior theoretical structure and the tools for the estimation and analysis of the dynamic behaviour of such models are widely available. An early VAR analysis in this area is the one by Lee (1992) and more recent ones are by Cheung and Ng (1998) and Gjerde and Saettem (1999). One of the costs of the atheoretical nature of the VAR is that the shocks in the model are difficult to interpret in economic terms. Indeed, if we view the VAR as a reduced form of a structural model, its error terms will be linear combinations of various structural errors. Thus, in a reduced-form VAR real output innovations will generally be combinations of supply and demand shocks that are not distinguished even though theory predicts that they may well have quite different effects on stock prices. A recent strand of VAR models has imposed extra structure on the VAR in an attempt to overcome the difficulty in the interpretation of the shocks. Starting with Bernanke (1986), Sims (1986), Blanchard (1989a) and Blanchard and Quah (1989), methods were devised to restrict the generality of the VAR by imposing restrictions based on prior theorising, thus enabling the interpretation of the shocks in terms of the theoretical priors. Sims, Bernanke and Blanchard, all used short-run restrictions while Blanchard and Quah based their restrictions on the long-run relations between the variables. Subsequent work such as that by Gali (1992) has combined these two types of restrictions. While original applications of these structural VARs (SVARs) were in the area of macroeconomics (and this continues to be a focus, see e.g. Rapach, 1998), in recent years applications have also been to financial economics. In a series of papers, Lee et al. have applied SVAR models to the analysis of stock markets. In Lee (1995), Lee (1998) and Chung and Lee (1998) the focus was on the decomposition of stock prices into temporary and permanent components using models including financial variables, such as dividends, earnings and interest rates. In Hess and Lee (1999), the same technique was applied to address the puzzle that stock returns are generally found to be negatively related to inflation, a puzzle which is at least partially resolved by using the model to distinguish between demand and supply shocks. All of the Lee et al. papers use the Blanchard and Quah identification procedure based on long-run restrictions. Another series of papers by Gallagher and Taylor also focus largely on the decomposition of stock prices into temporary and permanent components using the Blanchard–Quah identification scheme, although, in contrast to the Lee et al. papers, the identification proceeds using inflation rather than financial variables as the additional identifying variable. In Gallagher (1999), the Blanchard and Quah procedure is applied to a VAR in two variables (stock prices and inflation) to identify temporary and permanent components in stock prices for 16 European countries while in Gallagher and Taylor (2000), a similar technique is applied to US data, using nominal interest rates as the second identifying variable in the place of inflation and applying estimation techniques which are robust to the usual departures from iid-normality common in financial data. In Gallagher and Taylor (2002a), the focus is, like Hess and Lee (1999), on the stock-price–inflation puzzle, which is analysed in a model containing only these two variables. In Gallagher and Taylor (2002b), the model is again a two-variable VAR in inflation and stock returns, which is used to decompose stock prices into temporary and permanent parts using the Blanchard and Quah procedure. In the latter paper, however, the restrictions used for identification are based on a simple macroeconomic model, which allows the distinction between demand- and supply-driven components of inflation. In the present paper, we pursue this distinction between demand and supply shocks but apply it to output, rather than to inflation, since our interest is in the relationship between output and stock prices and, in particular, between the demand- and supply-driven components of output on the one hand and stock prices on the other. Moreover, we argue that the identification of demand and supply components proceeds more naturally in terms of output than inflation or interest rates. We, therefore, begin by developing a macro model of the Blanchard and Quah type extended to include stock prices and use it as the basis for the identification of demand and supply components of the output innovations in a framework which includes the unemployment rate, in addition to output and stock prices, as the additional identifying variable in the spirit of the original Blanchard and Quah scheme. Our approach has most in common with a recent paper by Rapach (2001), which extends his earlier work, Rapach (1998), but uses a more extensive model and a different identification scheme to the one we propose. In addition to allowing the analysis of the relative effects of supply and demand shocks on real and financial variables, our empirical model also allows for an analysis of the relative effects of stock market (portfolio) shocks on output, unemployment and the stock market itself, and hence the importance of such shocks to the real economy. Further, in order to characterise the sources of stock price fluctuations, we decompose stock prices over the sample period. Our model is sufficiently rich in structure to allow two interesting decompositions. The first uses a distinction between permanent and temporary components based on our identifying scheme; and the second distinguishes between real economy and stock market components of stock price fluctuations, which, as far as the authors are aware, have not been considered by the existing literature. The only temporary shock in our model is a demand one so that the temporary component of stock prices is that component which results from demand-driven output fluctuations with supply-based output fluctuations and stock market shocks both having permanent effects. The real/stock market decomposition separates demand and supply influences on the one hand from stock market shocks on the other. Utilising these decompositions provides an opportunity to analyse the changing characteristics of real stock price fluctuations. The structure of our paper is as follows. In Section 2, we set out a simple macro model, which we use to motivate our restrictions. In Section 3, we set out the SVAR and explain the way in which we identify the demand and supply shocks and compute the decomposition of stock prices into demand and supply components. We go on in Section 4 to a discussion of the data used, including tests of stationarity and cointegration before turning to a discussion of our results in Section 5. Conclusions are presented in Section 6.

In this paper, we have set out a small theoretical macro model of the relationship between stock prices and output and used it to restrict a vector-autoregressive model in the unemployment rate, real output and real stock prices, which we estimated using quarterly US data for the period 1947–2002. We identified three different structural shocks: a supply shock, a demand shock and a stock market or portfolio shock. The supply shock was allowed to have permanent effects on output and stock prices but not on the unemployment rate, the demand shock was identified as having only temporary effects on all our three variables and the stock market shock had long-run effects on real stock prices but only short-run effects on real output and the unemployment rate. The results reported in this paper suggest the following. First, there are asymmetries in the stock market–real economy relationship with the real economy having a more pronounced effect on the stock market than vice versa (at least over the sample period analysed here). Second, the influence from the real economy to the stock market is less important than shocks that are peculiar to the market itself. Third, supply and demand shocks have a relatively greater impact on stock prices than they do on real economy variables, such as unemployment and output, implying that the financial sector of the economy in general and stock market players, in particular, are particularly exposed to such shocks. Fourth, the evidence reported suggests that while the effects of stock market sentiment on stock prices has had a dominant role to play in the permanent component (supply-driven output fluctuations and stock market sentiment-driven fluctuations) of stock prices, since the mid-1990s, in particular, the sensitivity of real stock prices to supply fluctuations has waned considerably with almost all the variability of the permanent component being due to stock market sentiment. Further, the evidence also suggests that since the mid-1990s, the sensitivity of real stock prices to demand-driven output fluctuations has increased. Such observations suggest that stock price sensitivity to the real economy and financial influences not only changes over time but that stock price behaviour pre- and post-mid-1990s, in particular, differs.