Section 6 draws some implications for research in macroeconomics,including the modelling of investment,labor supply,and the welfare costs of economic fluctuations. 9
" 9 # % % # # 7 1
2 International Stock Market Data The stylized facts described in the previous section apply to postwar quarterly US data.Most empirical work on stock prices uses this data set,or a longer annual US time series originally put together by Shiller (1981).But data on stock prices,interest rates,and consumption are also available for many other countries. In this chapter I use an updated version of the international developed-country data set in Campbell (1999).The dataset includes Morgan Stanley Capital International (MSCI) stock market data covering the period since 1970.I combine the MSCI data with macroe- conomic data on consumption,short-and long-term interest rates,and the price level from the International Financial Statistics(IFS)of the International Monetary Fund.I am able to use consumption of nondurables and services for the US,but must use total consumption expenditure for the other countries in the dataset.For some countries the IFS data are only available quarterly over a shorter sample period,so I use the longest available sample for each country.Sample start dates range from 1970.1 to 1982.2,and sample end dates range from 1997.4 to 1999.3.I work with data from 11 countries:Australia,Canada,France,Germany, Italy,Japan,the Netherlands,Sweden,Switzerland,the United Kingdom,and the United States. For some purposes it is useful to have data over a much longer span of calendar time. I have been able to obtain annual data for Sweden over the period 1920-1998 and the UK over the period 1919-1998 to complement the US annual data for the period 1891-1998.The Swedish data come from Frennberg and Hansson (1992)and Hassler,Lundvik,Persson,and Soderlind (1994),while the UK data come from Barclays de Zoete Wedd Securities (1995) and Economist (1987).4 In working with international stock market data,it is important to keep in mind that different national stock markets are of very different sizes,both absolutely and in proportion 4The annual data end in 1994 or 1995 and are updated using the more recently available quarterly data Full details about the construction of the quarterly and annual data are given in a Data Appendix available on the author's web page.Dimson,Marsh,and Staunton (2002)report summary statistics for a more comprehensive long-term annual international dataset. 10
$ !" * ( ( # % !" % % " A14B = ( # # - - ) A111B *% " - A*"-B ( ( % 13 - *"- ) # ) %) # - " A-"B - * - !"# ' -" $ # - % " % 13 14# % 1132 1116 - ( ; # # # + # - # # M # " # " # ! F% # ! " % - " 1)114 !F 11)114 !" 41)114 " % ? A11B ? # : (# @ # "N A112B# !F = K G " A118B . A143B - (% ( ( # ( J ( ( J # 2- + #**) #**E - + + + F + ?++ + - - F + + A + + - -G = - & C"!!"D - + + +
to national GDP's.Campbell(1999,Table 1)reports that in the quarterly MSCI data for 1993 the Japanese MSCI index was worth only 65%of the US MSCI index,the UK MSCI index was worth only 30%of the US index,the French and German MSCI indexes were worth only 11%of the US index,and all other countries'indexes were worth less than 10%of the US index.The US and Japan together accounted for 66%of the world MSCI capitalization, while the US,Japan,the UK,France,and Germany together accounted for 86%.The same table shows that different countries'stock market values are very different as a fraction of GDP.If one thinks that total wealth-output ratios are likely to be fairly constant across countries,then this indicates that national stock markets are very different fractions of total wealth in different countries.In highly capitalized countries such as the UK and Switzerland, the MSCI index accounted for about 80%of GDP in 1993,whereas in Germany and Italy it accounted for less than 20%of GDP.The theoretical convention of treating the stock market as a claim to total consumption,or as a proxy for the aggregate wealth of an economy,makes much more sense in the highly capitalized countries.5 Table 1 reports summary statistics for international asset returns.For each country the table reports the mean,standard deviation,and first-order autocorrelation of the real stock return and the real return on a short-term debt instrument.6 The first line of Table 1 gives numbers for the standard postwar quarterly US data set summarized in the introduction.The top panel gives numbers for the 11-country quarterly MSCI data,and the bottom panel gives numbers for the long-term annual data sets.The table shows that the first four stylized facts given in the introduction are fairly robust across countries. 1.Stock markets have delivered average real returns of 4.5%or better in almost every 5Stock ownership also tends to be much more concentrated in the countries with low capitalization.La Porta,Lopez-de-Silanes,Shleifer,and Vishny (1997)have related these international patterns to differences in the protections afforded outside investors by different legal systems. 6As explained in the Data Appendix,the best available short-term interest rate is sometimes a Treasury bill rate and sometimes another money market interest rate.Both means and standard deviations are given in annualized percentage points.To annualize the raw quarterly numbers,means are multiplied by 400 while standard deviations are multiplied by 200(since standard deviations increase with the square root of the time interval in serially uncorrelated data). 11
+&@H A111# B $ *"- 116 *"- ' 985 !" *"- '# !F *"- ' 65 !" '# + *"- ' 5 !" '# H ' 5 !" ' !" % 995 *"- # !"# # !F# # + % 495 J H ( ( J +&@ - ( ) ( # ( ( J J - % !F " # *"- ' 45 +&@ 116# + - 5 +&@ % ( ( # ' %% % # ( % # # ) ( ) % $ !" % ) $ *"- # % %) % " ( ( % 285 & < = - + - - = - += +4 8 4 &+ &-+ : - C#**(D - + - + H - H H + + A+ - A - + + - 2 ++ - < - +4 2 +4 - = F + + + )!! =-+ + + "!! C = - - F - + ++ + D
country and time period.The exceptions to this occur in short-term quarterly data,and are concentrated in markets that are particularly small relative to GDP (Italy,3.2%),or that predominantly represent claims on natural resources (Australia,3.5%).The very poor performance of the Japanese stock market in the 1990's has reduced the average Japanese return to 4.7%. 2.Short-term debt has rarely delivered an average real return above 3%.The exceptions to this occur in two countries,Germany and the Netherlands,whose sample periods begin in the late 1970's and thus exclude much of the surprise inflation of the oil-shock period. 3.The annualized standard deviation of stock returns ranges from 15%to 27%.It is striking that the market with the highest volatility,Italy,is the smallest market relative to GDP and the one with the lowest average return. 4.In quarterly data the annualized volatility of real returns on short debt is 2.9%for the UK,2.8%for Italy and Sweden,2.5%for Australia,2.3%for Japan,and below 2%for all other countries.Volatility is higher in long-term annual data because of large swings in inflation in the interwar period,particularly in 1919-21.Much of the volatility in these real returns is probably due to unanticipated inflation and does not reflect volatility in the ex ante real interest rate. These numbers show that high average stock returns,relative to the returns on short- term debt,are not unique to the United States but characterize many other countries as well.Recently a number of authors have suggested that average excess returns in the US may be overstated by sample selection or survivorship bias.If economists study the US because it has had an unusually successful economy,then sample average US stock returns may overstate the true mean US stock return.Brown,Goetzmann,and Ross(1995)present a formal model of this effect.While survivorship bias may affect data from all the countries included in Table 1,it is reassuring that the stylized facts are so consistent across these countries.7 7Jorion and Goetzmann(1999)consider international stock-price data from earlier in the 20th Century and argue that the long-term average real growth rate of stock prices has been higher in the US than elsewhere.However they do not have data on dividend yields,which are an important component of total return and are likely to have been particularly important in Europe during the troubled interwar period. 12
' ) $ # ( +&@ A- # 65B# A; # 685B ( ( 11H % 235 ") % 65 ' # + M # % 13H ' 7 ) ( 6 ( % 85 35 - (% ( % # - # ( +&@ % 2 - $ 15 !F# 45 - " # 85 ; # 65 # 5 L % %) % % 7 # 11) * 7 7 ' % % ( # ) # $ ! " 0 %% % ' !" - !" # % !" ( !" ( = # + # 0 A118B J G J # % 5 3 4 C#***D + < + - "! - - - + + = - < - - - - & - + =- = - - + =-- + +< + - ++ - + =
Table 2 turns to data on aggregate consumption and stock market dividends.The table is organized in the same way as Table 1.It illustrates the robustness of two more of the stylized facts given in the introduction. 5.In the postwar period the annualized standard deviation of real consumption growth is never above 3%.This is true even though data are used on total consumption,rather than nondurables and services consumption,for all countries other than the US.Even in the longer annual data,which include the turbulent interwar period,consumption volatility slightly exceeds 3%only in the US. 6.The volatility of dividend growth is much greater than the volatility of consumption growth,but generally less than the volatility of stock returns.The exceptions to this occur in countries with highly seasonal dividend payments;these countries have large negative autocorrelations for quarterly dividend growth and much smaller volatility when dividend growth is measured over a full year rather than over a quarter. Table 3 reports the contemporaneous correlations among real consumption growth,real dividend growth,and stock returns.It turns out that these correlations are somewhat sensi- tive to the timing convention used for consumption.A timing convention is needed because the level of consumption is a flow during a quarter rather than a point-in-time observation; that is,the consumption data are time-averaged.s If we think of a given quarter's con- sumption data as measuring consumption at the beginning of the quarter,then consumption growth for the quarter is next quarter's consumption divided by this quarter's consumption If on the other hand we think of the consumption data as measuring consumption at the end of the quarter,then consumption growth is this quarter's consumption divided by last Dimson,Marsh,and Staunton(2002)do have dividend yields for the early 20th Century and find that US stock returns were not extraordinarily high relative to other countries in that period.Li and Xu(2002)argue that survival bias can be large only if the ex ante probability that a market fails to survive is unrealistically large. sTime-averaging is one of a number of interrelated issues that arise in relating measured consumption data to the theoretical concept of consumption.Other issues include measurement error,seasonal adjustment,and durable goods.Grossman,Melino,and Shiller(1987),Wheatley (1988),Miron (1986),and Heaton (1995) handle time-averaging,measurement error,seasonality,and durability,respectively,in a much more careful way than is possible here,while Wilcox(1992)provides a detailed account of the sampling procedures used to construct US consumption data. 13
%% % ( ( % - % 8 - % 65 % # # !" . % # # % ' 65 !" 9 % % % # % ( ' % > % % $ % % $ 6 % % # % # ( - ) % ; % 7 % $ )) > # ) % - ( % $ H ) % %% $ # % $ ' $ H $ H - ( % $ # % $ H - & C"!!"D - + - + "! - @ - & < = A + - - + - - I C"!!"D - + + + - A + - < + + ++ + 2 + - + - - + J - + + , + 3 + &-++ C#*%(D /- + C#*%%D C#*%'D C#**ED -+ + + + - + = - + - =-+ /+A C#**"D + - + & 6