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Previous research finds that fundamental mac- roeconomic news has little effect on




Stock Prices, News, and Business;Conditions;Grant McQueen;Brigham Young University;V. Vance Roley;University of Washington;Previous research finds that fundamental mac- roeconomic news has little effect on;stock prices. We show that after allowing for different stages of the business cycle, a;stronger relationship between stock prices and news is evident. In addition to stock;prices, we examine the effect of real activity news on proxies for expected cash cows;and equity discount rates. We find that when the economy is strong the stock market;responds negatively to news about higher real economic activity. This negative;relation is caused by the larger increase in discount rates relative to expected;cash flows.;Apart from some types of monetary information, there is little empirical evidence to;support the hypothesis that stock prices respond to macroeconomic news. Schwert (1981);finds that the daily response of stock prices to news about inflation from 1953 to 1978 is;weak and slow. Pearce and Roley (1985) use survey data to measure expectations and find;that daily stock prices respond to monetary information between Sep- tember 1977 and;October 1982, but news about the consumer price index, unemployment, and industrial;We are grateful to Lynda S. Livingston and Steven R. Thorley for research assistance, to Stephen J. Brown (the editor);Wayne E. Fetson, Douglas K. Pearce, J. Michael Pinegar. James M. Poterba. Simon M. Wheatley, an anon- ymous referee;and seminar participants at the National Bureau of Economic Research and the University of Washington for helpful;comments, and to the Center for the Study of Financial Management, University of Washington, and Seafirst Bank, for;research support. Address correspondence to V. Vance Roley, Department of Finance, DJ-10, University of Washington, Seattle;WA 98195.;production have no significant effect on prices. Hardouvelis (1987);considers a somewhat broader set of variables through August 1984;and concludes that stock prices respond primarily to monetary news.;Finally, Cutler, Poterba, and Summers (1989) use vector autoregressions to measure news about macroeconomic time series from 1871;to 1986. They conclude that less than one-third of the monthly return;variance can be explained from these sources.;Each of these studies assumes that investors response to news is;the same over different stages of the business cycle. For instance;Cutler, Poterba, and Summers (1989) implicitly assume that a positive;surprise in industrial production at the end of the Great Depression;evokes the same response as a surprise in late 1969, after nearly a;decade of expansion. A positive surprise in industrial production;during the depression could indicate the end of the depression and;higher forecasts of firms cash flows. Such an announcement would;likely be good news for the stock market. In late 1969, with low;unemployment and factories running near full capacity, a positive;surprise in industrial production may result in fears of an overheating;economy, inflation, and possible efforts by policymakers to increase;real interest rates. Such an announcement could then be bad news;for the stock market. If the same type of news is considered good in;some states of the economy and bad in others, the response coefficient;on the surprise in previous studies will be biased toward zero.2;The popular press uses this good news/bad news story to interpret;daily stock price movements. For example, on February 4, 1983, after;16 months of recession, the Labor Department reported that the unemployment rate fell to 10.4 percent. This represented a rate of 0.2 or;0.3 percentage points below what was expected. This news was used;by the media to explain the 13.25-point jump in the Dow Jones Industrial Average, and prompted the Chairman of the Council of Economic;Advisers, Martin Feldstein, to comment that a recovery is either;beginning or already here (Wall Street Journal, February 7, 1983).;In contrast, on November 4, 1988, after six years of expansion, the;Labor Department reported that the unemployment rate fell to 5.3;percent, matching a 14-year low. This represented a rate of 0.1 or 0.2;percentage points below what was expected. The medias interpreta1;Chen, Roll, and Ross (1986) also investigate whether monthly stock returns covary with various;macroeconomic variables. They again find that the explanatory power is low. The main focus of;their study, however, is whether the covariance of economic variables with stock returns can explain;ex ante returns.;2;Several recent studies find significant effects from business conditions on stock returns. Ferson and;Merrick (1987). for example, find shifts in consumption-based asset pricing parameters across;stages of the business cycle measured by recession versus nonrecession. Fama and French;(1989) and Fama (1990) consider term-premium and default-risk-premium variables as;determinants of equity discount rates. They suggest that the term premium is related to NBER;business cycles, while the risk premium is related to business conditions over longer periods.;684;tion in this instance was bond market investors reacted with gloom;sending interest rates higher on fears of tighter Fed policy. The stock;market also fell (Wall Street Journal, November 7, 1988). The problem with this type of evidence, however, is that it is anecdotal and;largely after the fact.;In this article we examine whether the response of stock prices to;macroeconomic news varies over different stages of the business cycle.;By allowing the response to vary over different states of the economy;we can test the good news/bad news story and provide unbiased;estimates of the effects of fundamental information about the economy. We study daily percentage changes in closing values of the;Standard & Poors 500 Index and several variables related to equity;discount rates and cash flows. By considering these other variables;we can investigate the sources of any business-condition effect on;the response of stock prices.;Following this introductory section, we present in Section 1 a simple theoretical framework to consider how news affects stock prices;and how this effect can vary over different stages of the business cycle.;We describe the data in Section 2. In Section 3 we present the empirical results. We consider the robustness of the results in Section 4;and we summarize the main conclusions in Section 5.;1. Theoretical Framework;A common model that links stock prices to information posits that;stock prices equal the present discounted value of rationally forecasted future dividends. This model can be represented as;where P, is the price of the stock at time;denotes the mathematical expectation conditional on information available at time t;is the dividend paid at time;is the stochastic;discount factor for cash flows that occur at time;Economic announcements affect daily share price movements if the;new information revealed by announcements affects either expectations of future dividends or discount rates or both. The new information is represented by the difference in the announced value on;day t + 1 and the expected value as of day t. Consequently, the;unanticipated component of an announcement on day t + 1 is uncorrelated with information available on day t. The information set;includes past announcements of other economic variables, so;announcement surprises are uncorrelated under rational expectations;if they are made on different days. Combining daily stock-price changes;685;with announcement surprises on different days allows us to isolate;the effects of individual economic variables.;1.1 Impact of real economic activity surprises;We need not expect that real economic activity surprises will affect;cash flows and discount rates in the same way across different states;of the economy. As a result, stock prices may well react differently to;surprises of this nature, depending on whether the economy is operating below capacity. When the economy is booming, for example, a;real economic activity surprise could result in a larger increase in;discount rates than cash flows, causing stock prices to fall. In this;case, high capacity utilization and employment may constrain further;increases in output and, consequently, cash flow in the absence of;new investment in plant and equipment.;The announcement effect we examine corresponds to the disclosure in month t of production growth that already occurred in month;t - 1. Information about the previous month is relevant in that it may;change expectations about the future. That is, consistent with Fama;(1990) and Schwert (1990), the information provided by an industrial;production announcement causes stock prices to respond if this information causes revisions in expected future industrial production.;1.2 Impact of other economic announcement surprises;We also consider possible asymmetric effects of announcement surprises other than those related to real economic activity. This other;economic information is, however, less closely related to the possible;business-conditions effects discussed above. The announcements we;consider are for foreign trade, inflation, and money. We briefly discuss;each in turn.;First, foreign trade deficit announcements have at times received;considerable attention in the popular press. For the 1979-1984 period;however, Hardouvelis (1987) does not find any significant effects on;stock prices. We update his sample and test for varying effects over;different economic states.;Second, following the empirical studies of Nelson (1976) and Fama;and Schwert (1977), a number of studies estimate a significant negative relationship between inflation and stock returns. Among these;Feldstein (1980) argues that the tax treatment of depreciation and;inventories results in lower real after-tax corporate profits and, hence;lower stock prices during times of inflation. Fama (1981), Geske and;Roll (1983), and Kaul (1987) explain the negative relationship by;appealing to real output effects. In terms of inflation announcement;surprises, the significance of the stock-price response is mixed [e.g.;Pearce and Roley (1985) and Hardouvelis (1987)]. We again extend;686;these announcement studies by lengthening the sample and by allowing business-condition-dependent responses.;Third, Pearce and Roley (1983, 1985), Cornell (1983), and Hardouvelis (1987) find that stock prices respond significantly to money;announcement surprises. Varying responses over different monetary;policy regimes are tested in these studies, but possible businessconditions effects are not considered.3 We estimate the stock-price;response not only to money announcements but also to Federal Reserve;discount rate changes, over different economic states.;2. Data;Our sample period begins in September 1977 and ends in May 1988.;The start of the sample period coincides with the initial availability;of survey data from Money Market Services International (MMS). We;discuss the robustness of the results using alternative sample periods;and expectation measures in Section 4.3.;2.1 Asset prices and yields;We use daily percentage changes in the closing value of the S&P 500;Index to estimate the response of stock prices to new macroeconomic;information. For economic announcements occurring either before;or while the stock market is open, we use the percentage change in;the index from the previous business days closing price to the closing;price on that day. For announcements made after the stock market is;closed, we use the percentage change in the index from that days;closing quote to the next business days closing quote. Throughout;the sample, the stock market closed at 4:00 P.M. EST. (We use EST;for all closing and announcement times.);To measure the response of equity discount rates to new information, we consider several proxies. These include daily changes in;the three-month Treasury-bill and lo-year Treasury-bond yields. Following Fama and French (1989) and Fama (1990), we also include;variables denoted as the term spread and the default spread as equity;discount rate proxies. We represent the term spread by Moodys Aaa;corporate bond yield minus the three-month bill yield, and the default;3;Given the evidence that both short- and long-term interest rates respond differently to money;announcement surprises over different Federal Reserve policy regimes [e.g., Roley (1983, 1986).;Cornell (1983), and Roley and Walsh (1985)], another potentially interesting hypothesis is that;stock prices respond differently to economic news over these regimes. For the October 1979 and;October 1982 regimes, however, Pearce and Roley (1983, 1985) and Hardouvelis (1987) find no;significant difference in the stock markets response to money surprises. We nevertheless investigate;the effects of the monetary policy regimes in October 1979, October 1982, and February 1984. and;the hypothesis that the stock markets response is the same across regimes for our set of economic;announcements can be rejected only at the 25 percent significance level. Consequently, we do not;examine the effects of monetary policy regimes further.;687;spread by Moodys Baa corporate bond yield minus the Aaa yield.;These yield data are from the Federal Reserves H.15 release, and;they correspond to yields based on bid prices prevailing at 3:30 P.M.4;2.2 Economic announcements;Virtually all of the economic announcements are well-publicized;events with regular schedules. Data on industrial production (IP) are;initially released, seasonally adjusted monthly percentage changes in;the Federal Reserve Industrial Production Index, all items. Between;January 1979 and October 1985, the announcements were made at;9:30 A.M., since October 1985, at 9:15 A.M. Before 1979, the industrial;production press releases give no specific announcement time, stating;only for immediate release. However, the announcements were;made before the market opened for our sample.;Data on the unemployment rate (UNEM) and the percentage change;in nonfarm payroll employment (NFP) are based on the initial;announcements by the Bureau of Labor Statistics, and both are seasonally adjusted. We convert the announced nonfarm payroll employment data into percentage changes from the previous months;announced level. During our sample period, both the unemployment;rate and payroll employment announcements were made at the same;time, typically the first Friday in the month. Each announcement may;however, contain unique information, since they are based on two;different surveys. The unemployment data are collected from a survey;of households, conducted and tabulated by the Bureau of the Census;for the Bureau of Labor Statistics. The payroll employment data are;collected by state agencies from payroll records of employers and are;tabulated by the Bureau of Labor Statistics. These employment data;were announced at 9:00 A.M. through March 1982 and at 8:30 A.M. from;April 1982 to the present.;The merchandise trade deficit (MTD) is announced by the Foreign;Trade Division of the Department of Commerce, and it represents;the seasonally adjusted monthly trade deficit in billions of dollars;(trade surpluses are negative). For most of the sample period, these;announcements give information on the preceding months deficit.;Starting in March 1987, the announcements were delayed several;weeks. So, an announcement in March, for example, would give information on Januarys trade deficit. Between February 1979 and November 1983, the announcements were made at 2:30 P.M., and in December 1983 it was made at 9:30 A.M. Since January 1984, the;announcements have been made at 8:30 A.M.;4;We also use the 10-year Treasury-bond yield in the term and default spreads, replacing the Aaa;yield. The test results reported in the next section ate qualitatively the same using these alternative;definitions.;688;The data on inflation are seasonally adjusted monthly percentage;changes in the Consumer Price Index (CPI) and Producer Price Index;(PPI) as announced by the Bureau of Labor Statistics. Beginning in;February 1978, we use the CPI-U (all urban consumers), consistent;with the MMS expectations data. The PPI series corresponds to all;finished goods, again consistent with the MMS expectations data. The;PPI and CPI announcements were made on various days near the;middle of each month. The PPI announcement is, however, made;earlier in the month than the CPI announcement. With three exceptions, the inflation announcements were made before the stock market;opened, specifically at 9:00 A.M. before March 1982 and at 8:30 A.M.;from April 1982 to the present.5;The money stock data consist of seasonally adjusted weekly percentage changes in M1, as announced in the Federal Reserves H.6;release. We convert the M1 data into percentage changes from the;previous weeks announced level. Before January 31, 1980, the;announcements were made on Thursdays at 4:10 P.M., and they corresponded to changes in old M1. Then, the announcements were;made at 4:10 P.M. on Fridays, and they corresponded first to Ml-B and;then to MI, where this latter M1 is equivalent to M1-B.6 Beginning;on November 29, 1982, money announcements were made at 4:15;P.M. Starting on February 16, 1984, money announcements were;switched back to Thursdays, and since March 22, 1984, they have;been made at 4:30 P.M. Changes in the Federal Reserves discount;rate and surcharge were announced intermittently with no typical;announcement day or time.;2.3 Expected values of announcements;We use the survey data compiled by MMS International to form measures of the markets expectation of economic announcements. For;Ml, the survey data start on September 27, 1977. The survey data for;the CPI, PPI, and the unemployment rate begin in November 1977.;For industrial production, the data begin in December 1977. For the;merchandise trade deficit and nonfarm payroll employment, the survey data begin in February 1980 and February 1985, respectively. No;survey data are available for discount rate and surcharge announcements. As a consequence, all such changes are treated as unantici-;5;The PPI announcements in October 1981 and August 1985 were made at 2:00 P.M., and the;February 1979 CPI announcement was made at 2:30 P.M.;6;Old M1 differs from the current definition mainly in that it excludes other checkable deposits;at depository institutions. Following the introduction of nationwide NOW accounts in 1981, this;category became substantial;689;pated.7 Finally, we convert the survey data for M1 and nonfarm payroll;employment into expected percentage changes from the previously;announced level.;Although not reported here, we subject the survey data to unbiasedness and efficiency tests for the entire sample period and over;various subsamples [e.g., Pearce and Roley (1985)]. The overall results;of these tests are mixed. While the survey data are not always unbiased;and efficient, they generally have smaller root-mean-square errors;than autoregressive models. To correct for any systematic biases, as;well as to update the survey data with new information, we form;revised expectations [e.g., Roley (1983, 1985) and Shiller, Campbell;and Schoenholtz (1983)]. Since the survey can be taken as long as;five business days before an announcement, we use the change in;the three-month Treasury-bill rate over the four business days before;an announcement as the new information proxy. We estimate regression equations for each calendar year to form revised expectations.8;2.4 Classification of economic states;To test the hypothesis that the stock markets response to news varies;over business conditions, some classification of different levels of;economic activity is required. NBER business cycle turning points;are one possibility, but they classify the direction of economic activity;(i.e., expansion or recession) rather than the level. Unfortunately;widely accepted definitions analogous to NBER reference cycles are;not available for relative levels of economic activity.;In this article, we define economic states using several alternative;economic variables. For most of the reported results, we use the;seasonally adjusted monthly industrial production index, all items;(1977 = 100), to define economic states. First, we estimate a trend;in the log of industrial production by regressing the actual log of;industrial production on a constant and a time trend from September;1977. Then we add and subtract a constant from the trend, creating;7;Roley and Troll (1984) also make this assumption. Other researchers. however, attempt to forecast;discount rate changes. See, for example, Smirlock and Yawitz (1985). Batten and Thornton (1984).;and Hakkio and Pearce (1988). We do not use these approaches because they cannot isolate the;specific day in which the change is expected to occur. In contrast to these approaches, Cook and;Hahn (1988) simply classify changes into unexpected and expected categories based on Federal;Reserve statements.;8;When an economic announcement;is made before the market opens, the revised expectation is;the within-sample fitted value of the equation;where;is the survey measure;is the 3-month Treasury-bill yield at the close of day t - 1.;ei is a random error term. and a, b, and care coefficients. We perform the regressions over calendar;years instead of economic states to avoid possible biases in later tests that examine the effects of;business conditions. We include the last few months of 1977 and the first live months of 1988 in;the 1978 and 1987 calendar years, respectively.;690;F igu re 1;Natural log of industrial production, actual and bounds (trend.028);the upper and lower bounds illustrated in Figure 1. We choose the;constant 0.028 so that the log of industrial production is above the;upper bound, denoted as high economic activity, 25 percent of the;time. The log of industrial production is below the lower bound;indicating low economic activity, about 25 percent of the time as;well. Medium economic activity is represented by the remaining;observations between the bounds. As we discuss in Section 4.1, the;empirical results are not very sensitive to moderate changes in the;bounds or different series used to classify the states.;3. Empirical Results;3.1 Response to economic announcements;We first examine the impact of new economic information on stock;prices, interest rates, and other discount rate proxies without conditioning on the state of the economy. The results for interest rates;the term spread, and the default spread are useful because they provide evidence that economic announcements contain relevant information for financial markets. Although there are over 3800 days in;our sample period, we estimate how the markets respond to news;only for the 932 days on which one or more announcements is made.;Our initial estimation uses the following specification;691;where;percentage change in stock prices or change in interest;rates (measured in basis points) from business day;t - 1 to business day t;1 9 vector of unanticipated components of economic;announcements, calculated as;1 9 vector of economic announcements;1 9 vector of expected economic announcements;1 4 vector of day-of-the-week dummy variables for;Monday through Thursday;error term;a, b = scalar and 9 1 vector of coefficients, respectively;Following Pagan (1984), ordinary least-squares (OLS) estimation of;Equation (2) results in consistent estimates of coefficients and standard errors in the absence of heteroskedasticity. In all tables, however;Whites (1980) procedure is used to calculate standard errors to take;possible heteroskedasticity into account [e.g., French, Schwert, and;Stambaugh (1987) and Schwert (1989));We report the results for Equation (2) in Table 1 for the September;1977-May 1988 sample.9 The first row in the table shows, for example;that the S&P 500 Index falls by 0.1 percent in response to an unanticipated increase in industrial production of 1 percentage point. The loyear bond yield and the three-month Treasury-bill yield increase by;5.5 and 9.5 basis points, respectively, in response to this same;announcement. While interest rates exhibit statistically significant;responses to most of the new economic information, stock prices do;not. The S&P 500 Index response coefficient is significant at the 5;percent level only for unanticipated components of Ml announcements. These unconditional results are similar to those of other studies using much shorter sample periods [e.g., Pearce and Roley (1985)].10;9;In addition to specification (2). we also obtain results for a specification including the expected;values of economic announcements The inclusion of these variables has no effect on the;estimated response coefficients, 6, since the measures of unanticipated announced changes;are uncorrelated with;by construction. Test results are also unaffected. Correlations among the;unanticipated components of economic announcements, with the exception of the correlations;between the discount rate and Ml with nonfarm payroll employment, are not significantly different;from zero. Even these two significant correlations are only -.089 and -.071, respectively. This;lack of correlation is not surprising since the announcements usually occur on different days, and;the expectations variables include information up to the time of an announcement.;10;Similar to other studies, R2 is very low for the S&P 500 regression. While Roll (1988) reports;higher R2s for daily data, his regressions relate individual stock returns to market returns. In;contrast, the regression we report in Table 1 considers daily movements in a proxy for the;market return.;Because we consider only selected economic announcements, and all other news is ignored, it is;not surprising that R2 is low.;692;Table 1;Response of stock prices and interest rates to economic news (932 announcement day;observations), September 1977-May 1988;* and ** indicate significance at the 10 and 5 percent levels, respectively. Term spread = Moodys;Aaa corporate bond yield minus the three-month Treasury-bill yield. Default spread - Moodys Baa;corporate bond yield minus the Aaa yield.;unanticipated percentage change in industrial;production (12/77-5/88. 126 observations).;unanticipated change in the unemployment;rate (11/77-5/88, 127 observations).;unanticipated percentage change in nonfarm payroll;employment (2/85-5/88, 40 observations).;unanticipated percentage change in the merchandise trade deficit (2/80-5/88, 100 observations).;unanticipated percentage change in;the Producer Price Index (1 l/77-5/88, 127 observations).;unanticipated percentage change;in the Consumer Price Index (11/77-5/88, 127 observations).;unanticipated percentage;change in the narrowly defined money stock (9/77-5/88, 557 observations).;unanticipated;change in the Federal Reserves discount rate (9/77-5/88, 38 observations).;multiple correlation coefficient corrected for degrees of freedom. SE = standard error. DW = Durbin-Watson;statistic. Estimation results are for specification (2). Standard errors of estimated coefficients are in;parentheses, and they are corrected for heteroskedasticity by using Whites (1980) procedure.;Changes in yields are from 3:30 P.M. to 3:30 P.M. on adjacent business days. Changes in stock prices;are from close to close on adjacent business days.;3.2 Response conditional on the state of the economy;We estimate the conditional responses to economic news, using the;following specification;where Ht = 1 if economic activity is in the high state at time t, and;zero otherwise, Mt = 1 if economic activity is in the medium state;and zero otherwise, and Lt = 1 if economic activity is in the low state;and zero otherwise. The other variables and coefficients are as defined;in Equation (2), and the regression again includes only announcement days.;693;Table 2;Response of stock prices to economic news in different states of the economy, September;1977-May 1988;estimated responses in Equation (3) in high and low states, respectively. F(m, n) =;F-statistic with (m, n) degrees of freedom. p value = probability of obtaining that value of the;F-statistic or higher under the null hypothesis. Estimation results are for specification (3). High;medium, and low states of economic activity are calculated relative to trend industrial production, as described in Section 2.4. Standard errors of estimated coefficients are in parentheses.;The number in brackets below the p value for H0 for;is an estimated p value from 1000 bootstrap;simulations. Standard errors and test statistics use Whites (1980) heteroskedasticity consistent;covariance matrix.;We report the results of Equation (3) in Table 2. In contrast to the;previous tables, the S&P 500 Index now responds significantly to a;variety of economic information when the response is made conditional on the state of the economy. In particular, the results suggest;that good news about economic activity in the high state is bad news;for the stock market. For a 1 -percentage-point unanticipated increase;in industrial production, stock prices decline by about 0.8 percent in;the high state. Similarly, we estimate that an unanticipated decline;in the unemployment rate of 1 percentage point causes stock prices;to decline by about 2.2 percent in the high state. The point estimates;694;of the responses to these two announcements change signs in the;low state, although these estimates are now not statistically significant.;The response coefficients are nevertheless significantly different from;the coefficients in the high state, as shown on the right-hand side of;Table 2 (H0). These results imply that previous estimates obtained;without any allowances for business cycle effects are biased toward;zero, contributing to the insignificant responses estimated in earlier;studies.;We estimate that unanticipated increases in both the merchandise;trade deficit and the PPI have significant negative effects on stock;prices in the high output state. Money announcement surprises affect;stock prices in both high and medium states, but the sign of the;response is the same across all three states. Finally, CPI announcements produce mixed results, with a positive coefficient in the high;state. However, a test of the hypothesis that the coefficients on CPI;and PPI surprises in the high state are the same has a p value of.138.;We test asymmetric stock-price responses for groups of economic;announcements on the bottom of Table 2. In the first row, we test;the hypothesis that all coefficients in the high and low economic;states are the same (bH = bL). This hypothesis can be rejected at less;than the 10 percent significance level. In the next three rows (H2H4), we examine the effects of different types of economic information. The hypothesis that the stock markets responses to industrial;production and unemployment rate surprises are the same across high;and low states (H2) can be rejected at low significance levels. However, hypotheses that the stock markets response to other types of;information-inflation (H3) and monetary (H4)-differs over high;and low states cannot be rejected at the 10 percent significance level.;We also disaggregate the industrial production and unemployment;rate surprises in Table 2 into positive and negative surprises in each;of three states. In the high state, positive and negative industrial;production surprises have estimated coefficients of -0.934 and -0.815;respectively. In the low state, the estimates are 0.131 and 0.125 for;positive and negative surprises, respectively. We obtain similar results;for unemployment rate surprises, except that positive unemployment;rate surprises in the low state have a small positive coefficient insignificantly different from zero. The null hypothesis that positive and;negative industrial production surprises have the same coefficients;within high and low states (i.e., the specification estimated in Table;2) has a p value of.989. The same hypothesis for unemployment rate;surprises has a p value of.263. These results suggest that the response;to news within high and low states is symmetric. Stock prices fall in;response to positive surprises about the economy in the high state.;695;When news about economic activity is weaker than expected, stock;prices increase.;An alternative explanation of the results for the real activity variables, especially for industrial production, is that they are an artifact;of selection bias. That is, since we form the economic states using;ex post industrial production, future industrial production and, therefore, current stock prices are likely to fall in response to any news in;the high state. If ex ante state definitions are available, selection bi


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