Finance - general decisions under uncertainty economics of information the principal-agent relationship social responsiblity capital markets and securities markets market microstructure intermediation efficiency of securities markets rates of return on securities risk portfolio selection equilibrium prices of risky assets measurement of investment performance valuation of common stocks accounting information and valuation interest rates debt and preferred stock options convertible securities and warrants hedging instruments - futures and forwards capital expenditures cost of capital new securities issues splits and stock dividends cash dividends company financing and capital structure leasing and project finance financial planning working capital mergers and corporate restructuring regulated industries foreign exchange real estate commodity markets and exhaustible resources other speculative markets human capital tax inflation econometrics and statistics

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

In recent years, a number of proposals have been advanced for the limitation of carbon emissions. Some have argued that such limits would be costless, but our analysis suggests that there is no free lunch. (See our forthcoming paper.) We have attempted to estimate the costs but not the global benefits of slowing down climate change through carbon limitations. All computations were performed in parallel for five geopolitical regions. Except for oil trade, these regions were treated independently-as though there were no opportunity for international trade in carbon rights. For stimulating ideas on the politics and economics of negotiating an agreement on greenhouse gas emission permits, see M. Grubb (1989). Whatever rule is adopted for the allocation of carbon emission rights, there are likely to be significant interregional differences in the value of these rights. International trade will be needed if economic efficiency is to be achieved. In the absence of such trade, there are likely to be significant distortions in the comparative advantage of individual locations for the production of tradeable basic materials such as primary metals. These distortions could lead to counterproductive regulations and new forms of nontariff barriers to trade. This paper is intended to quantify the potential for international trade in carbon emission rights

[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

[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