[The nature of information regulation depends on the informational efficiency of capital markets (see Beaver 1989, 152-71; Dyckman and Morse 1986, 82-91). Consequently, researchers in accounting and finance have spent considerable effort attempting to measure efficiency. Although this investigation has spanned many research designs and has been applied to many different information signals, empirical tests all suffer from the same basic problem: the benchmark of interest, an informationally efficient market, is unobservable. The asset price that would have prevailed in an efficient market must therefore be modeled, and the test of market efficiency is confounded with a test of the asset-pricing model. Because of this ambiguity, whenever a researcher claims to find an abnormal return based on some information signal another researcher invariably responds that risk was not adequately controlled. For instance, Bernard and Thomas (1989, 1990) present evidence that markets do not adequately adjust to quarterly earnings announcements (i.e., there is a significant post-announcement drift), while Ball et al. (1990) argue that the market adjustment may be correct if the level of risk during the announcement period is adequately controlled for. Unlike naturally occurring markets, the efficiency of a laboratory market can be measured directly by creating another "artificial" economy that is identical to the economy of interest, except that all information is fully disseminated. The price in the artificial economy is the efficient price by definition; it is determined endogenously and without reference to an asset-pricing model. Using this method of measuring a market's efficiency, this study investigates how efficiency is influenced by different information or market structures. Although such an investigation will not resolve the issue of whether naturally occurring markets are efficient, laboratory results can identify features of a market or information structure that aid or impede efficiency. The study compares two information structures that differ by whether there is aggregate certainty in the market; that is, whether the union of all traders' information signals perfectly identifies the value of the risky asset. Previous experimental research in market efficiency has used markets with aggregate certainty. However, many of the difficulties of decision making under uncertainty disappear when the information in the market collectively reveals the asset's payoff. On the other hand, for the experiments conducted here, there are relatively more signals to aggregate in the markets with aggregate certainty. The results show that in markets where different traders have different information signals, the presence of aggregate uncertainty significantly reduces efficiency relative to similar markets with aggregate certainty. However, the results also show that markets are very efficient when some traders have a common but imperfect information signal and other traders are uninformed. In these markets there is aggregate uncertainty but no diversity of information among informed traders. Thus, diversity of informed traders' information and aggregate uncertainty together lead to inefficient markets, but neither treatment by itself causes inefficiency. The study also manipulates the number of traders in the market. It is sometimes argued that markets are efficient because there are a large number of traders whose individual errors average out. However, there is no reason to believe that the asset-pricing relation applies equal weight to each trader's belief, so a central limit result may not hold. The results show that the number of traders has no significant impact on the efficiency of the final prices in a trading period. Within a trading period, however, markets with only a few traders converge to the efficient price much more quickly than do markets with many traders. The results also show that there is a greater diversity of behavior in the markets with many traders. It is possible that this increased diversity increases the number of "noisy" transactions, making it more difficult to infer information from market data. In any investigation of a market's efficiency, different traders must have different information at the time efficiency is being assessed; otherwise the market is efficient by definition. Although accounting disclosures are publicly available they can effectively generate different information signals to different traders. The markets presented here give two examples. In the aggregate certainty treatment, some traders received good news signals and other traders received bad news signals. An example of this type of information system is an economy where different traders having different earnings expectation models. In such an economy the same earnings report can be good news to some traders and bad news to other traders. As long as the "correct" earnings expectation model is unknown, each trader would find the other traders' signals-in this case their forecast errors-informative. In the number-of-traders treatment, some traders receive a signal while other traders do not. An example of this type of information system is an economy where some traders receive accounting disclosures very quickly by subscribing to a wire news while other traders receive the information via third-class mail. Here the uninformed traders would benefit by learning the informed traders' signal.]

Reviews the book "Competing Against Time: How Time-Based Competition Is Reshaping Global Markets," by George Stalk and Thomas M. Hout.

Examines the information content of announcements of increased reserves for loan loss by Citicorp and other banks, and the later write-off announcement made by the Bank of Boston in 1987. Bank accounting for loan losses; Study of the events surrounding the Citicorp and Bank of Boston announcements; Implication of Citicorp's increase in loan loss reserves.

The article investigates how capital markets efficiency is influenced by different information or market structures in the United States. The nature of information regulation depends on the informational efficiency of capital markets. Researchers in accounting and finance have spent considerable effort attempting to measure efficiency. Although this investigation has spanned many research designs and has been applied to many different information signals, empirical tests all suffer from the same basic problem: the benchmark of interest, an informationally efficient market, is unobservable. The asset price that would have prevailed in an efficient market must therefore be modeled, and the test of market efficiency is confounded with a test of the asset-pricing model. Because of this ambiguity, whenever a researcher claims to find an abnormal return based on some information signal another researcher invariably responds that risk was not adequately controlled. The efficiency of a laboratory market can be measured directly by creating another artificial economy that is identical to the economy of interest, except that all information is fully disseminated.

[During 1987, the climate of international bank lending changed dramatically and prompted major restatements of the loan portfolios of the largest U.S. money-center and regional banks. The circumstances involved decisions by several countries in Latin America-notably Brazil-to suspend scheduled interest and principal payments on their foreign debt. The exposure of the U.S. banks became most visible on February 20, 1987, when Brazil declared a moratorium on interest payments on 67 billion of medium- and long-term bank debt and, five days later, froze payments on 10 billion of short-term credits and $5 billion of money market deposits. A chain of events began in March 1987 and produced the largest reported losses in U.S. banking history. This article examines how the stockholders' returns of 13 of the largest U.S. money-center and regional banks were affected by disclosures made during 1987 regarding decisions to place Brazilian loans on a nonaccrual basis and to increase loan loss reserves to recognize the higher probability of default and the lower present value of future interest and principal. The study adds to the recent literature on banks' earnings and asset relations (Barth et al. 1990; Beaver et al. 1989) and to the accumulated evidence on the role of banks' accounting decisions in response to the resulting substantial asset impairment caused by the 1987 Latin American debt situation (Elliott et al. 1989; Grammatikos and Saunders 1990; Johnson 1989; Musumeci and Sinkey 1990a, 1990b). Using a methodology that focuses on the unanticipated short-term effects of the announcements, we find that the stock market responded adversely to the banks' reclassification of loans to the nonaccrual basis and positively to subsequent announcements of additions to loan loss provisions. The latter reaction is viewed as consistent with banks' use of those adjustments as credible signals about their intentions and abilities to resolve the Latin American debt situation. We also find that changes in secondary market prices for Brazilian loans explain banks' stockholders returns during the period and that returns measured over short intervals varied according to the balance-sheet amount of foreign loans. Such results are consistent with the hypothesis that the stock market discriminates among banks on the basis of reported foreign loan data.]

The article presents an overview of accounting and stock prices. These two types of study, which are actually market reaction and valuation studies, are not entirely distinct. In so far as it is concerned with price effects, the former type generally focuses on the relation between new accounting information and short-term changes in stock prices. Valuation studies, on the other hand, are ostensibly concerned with the relation between the level of stock prices and accounting variables, generally earnings but in order to mitigate problems arising from omitted variables, valuation studies frequently use first differences and also consider the relation between changes in stock prices and changes in earnings. However, the distinction between the two types of study may be maintained by observing that market reaction studies generally analyze security returns over much shorter time interval.

Reviews the book "Cheating the Government: The Economics of Evasion," by Frank A. Cowell.

[In this article, we examine the information content of announcements of increased reserves for loan loss by Citicorp and other banks, and the later write-off announcement made by the Bank of Boston. During 1987, most major U.S. banks, led by Citicorp on 19 May 1987, announced large increases in their loan loss reserves because of problem loans in lesser developed countries (LDC). With substantial flexibility in accounting rules for determining loss exposure, the banks announced varying levels of reserve increases. On 14 December 1987, the Bank of Boston began a second round of activity relating to LDC debt by announcing a $200 million write-off of LDC loans and further increase in loan loss reserves. Financial reporters suggested that these events could be interpreted differently. Because Citicorp was a leading money-center bank, its announcement could be interpreted favorably as a signal of willingness to deal with the LDC debt problem. This interpretation could similarly apply to other banks, especially the more exposed money-center banks. In comparison, the Bank of Boston announcement was portrayed in the press as detrimental to the money-center banks for two reasons. First, unlike a reserve increase, a write-off reduces a bank's capital adequacy ratio. Capital adequacy ratios are used by bank regulators in determining the need for, and the level of, supervisory intervention. Second, the write-off was construed as an effort by regional banks to exploit their relatively limited exposure to LDC loans as a competitive advantage in the domestic banking market. We find evidence consistent with the expectations of the financial press. The strongest stock-price increases associated with both the Citicorp announcement and the subsequent announcements of reserve increases by other banks were found for the banks with the greatest exposure to LDC debt. In contrast, those banks with the greatest exposure to LDC debt and with the largest reserves sustained the largest stock-price decreases at the Bank of Boston write-off announcement. The larger money-center banks sustained, on average, a three-day decline in value of 5 percent around the Bank of Boston announcement date.]

Varian (1985) and Karpoff (1986) showed analytically that trading volume is positively related to the degree of differing beliefs. This study provides empirical evidence on the postulated relationship. The exe tent of disagreement or dispersion in financial analysts' forecasts of annual EPS for a firm is employed as the proxy for agents' differing beliefs about the firm's prospects. The revision in analysts' mean EPS forecasts, from one month to the next, is used to control for the volume effects of the net information signals emanating during the period. While some researchers have addressed the relation between the level of trading and earnings announcements (Beaver 1968; Morse 1981), and between trading volume and the magnitude of earnings forecast errors (Bamber 1986, 1987), the impact of discordant expectations on trading volume has been the subject of more recent empirical examination (Comiskey et al. 1987; Ziebart 1990; Lang and Litzenberger 1989). The hypothesis tested in this study posits that the fraction of outstanding common shares traded is a positive function of both forecast dispersion and mean forecast revision. While most previous studies of volume have concentrated on specific accounting disclosures, this study examines the trading associated with an almost continuous flow of information about the sampled firms that analysts implicitly use in their periodic revisions of earnings forecasts. Hence, tests of the model become possible at several times during the year, independent of formal accounting events/disclosures. Monthly observations in each of the four years 1978 to 1981 are used for the sample of 420 calendar-year firms; total number of observations is 16,747 over 48 months. Generalized least squares (GLS) estimation is applied to observations pooled over time and cross-sections and for each of the four years separately. Ordinary least squares (OLS) estimations are also performed and reported for comparative purposes and also to assess the stability of the models in monthly cross-sections. The results indicate a significant positive association between the dispersion in analysts' forecasts of annual EPS and the volume of trading. A relatively stable and positive association is found even after controlling for the volume effects of the magnitude of monthly revisions in the mean analysts' (annual) EPS forecast. The evidence corroborates the theoretical result that the degree of heterogeneity in beliefs is a determinant of the intensity of trading.