This article examines the hypothesis that the superior return to so-called value stocks is the result of expectational errors made by investors. The authors study stock price reactions around earnings announcements for value and glamour stocks over a five-year period after portfolio formation. The announcement returns suggest that a significant portion of the return difference between value and glamour stocks is attributable to earnings surprises that are systematically more positive for value stocks. The evidence is inconsistent with a risk-based explanation for the return differential. Coauthors are Josef Lakonishok, Andrei Shleifer, and Robert Vishny.

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme .

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. The author tests for the existence of systematic errors using survey data on forecasts by stock market analysts. He shows that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.

In the last decade, economists have produced a considerable body of research suggesting that the historical origin of a country's laws is highly correlated with a broad range of its legal rules and regulations, as well as with economic outcomes. We summarize this evidence and attempt a unified interpretation. We also address several objections to the empirical claim that legal origins matter. Finally, we assess the implications of this research for economic reform.

We address the joint hypothesis problem in cross-sectional asset pricing by using measured analyst expectations of earnings growth. We construct a firm-level measure of Expectations Based Returns (EBRs) that uses analyst forecast errors and revisions and shuts down any cross-sectional differences in required returns. We obtain three results. First, variation in EBRs accounts for a large chunk of cross-sectional return spreads in value, investment, size, and momentum factors. Second, time variation in these spreads is predictable from that in EBRs, holding constant scaled price variables (as proxies for time varying required returns). Third, firm characteristics often seen as capturing risk premia predict disappointment of expectations and low EBRs. Overall, return spreads typically attributed to exotic risk factors are explained by predictable movements in non-rational expectations of firms’ earnings growth.

We revisit La Porta's finding that returns on stocks with the most optimistic analyst long‐term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.

We examine the effect of securities laws on stock market development in 49 countries. We find little evidence that public enforcement benefits stock markets, but strong evidence that laws mandating disclosure and facilitating private enforcement through liability rules benefit stock markets.

We assemble data on government ownership of banks around the world. The data show that such ownership is large and pervasive, and higher in countries with low levels of per capita income, backward financial systems, interventionist and inefficient governments, and poor protection of property rights. Higher government ownership of banks in 1970 is associated with slower subsequent financial development and lower growth of per capita income and productivity. This evidence supports “political” theories of the effects of government ownership of firms.

We use data on ownership structures of large corporations in 27 wealthy economies to identify the ultimate controlling shareholders of these firms. We find that, except in economies with very good shareholder protection, relatively few of these firms are widely held, in contrast to Berle and Means's image of ownership of the modern corporation. Rather, these firms are typically controlled by families or the State. Equity control by financial institutions is far less common. The controlling shareholders typically have power over firms significantly in excess of their cash flow rights, primarily through the use of pyramids and participation in management.