[We develop a model of the optimal initial public offering (IPO) decision in the presence of learning about the average profitability of a private firm. The entrepreneur trades off diversification benefits of going public against benefits of private control. Going public is optimal when the firm's expected future profitability is sufficiently high. The model predicts that firm profitability should decline after the IPO, on average, and that this decline should be larger for firms with more volatile profitability and firms with less uncertain average profitability. These predictions are supported empirically in a sample of 7183 IPOs in the United States between 1975 and 2004.]

We propose a general equilibrium model with multiple securities in which investors' risk preferences and expectations of dividend growth are time-varying. While time-varying risk preferences induce the standard positive relation between the dividend yield and expected returns, time-varying expected dividend growth induces a negative relation between them. These offsetting effects reduce the ability of the dividend yield to forecast returns and eliminate its ability to forecast dividend growth, as observed in the data. The model links the predictability of returns to that of dividend growth, suggesting specific changes to standard linear predictive regressions for both. The model's predictions are confirmed empirically.

Previous work on information and financial markets has focused on a special set of assumptions: agents have exponential utility, and random variables are normally distributed. These assumptions are often necessary to obtain closed-form solutions. We present an example with alternative assumptions, and demonstrate that some of the conclusions from previous literature fail to hold. In particular, we show that in our example, as more agents acquire information, prices do not necessarily become more informative, and agents may have greater incentive to acquire information. Learning can therefore be a strategic complement, allowing for the possibility of multiple equilibria.

We develop a general equilibrium model of government policy choice in which stock prices respond to political news. The model implies that political uncertainty commands a risk premium whose magnitude is larger in weaker economic conditions. Political uncertainty reduces the value of the implicit put protection that the government provides to the market. It also makes stocks more volatile and more correlated, especially when the economy is weak. We find empirical evidence consistent with these predictions.

We calculate the costs and benefits of the largest ever US government intervention in the financial sector announced during the 2008 Columbus-day weekend. We estimate that this intervention increased the value of banks’ financial claims by 130 billion (bn) at a taxpayers’ cost of 21–44 billion with a net benefit between 86 and $109bn. By looking at the limited cross section, we infer that this net benefit arises from a reduction in the probability of bankruptcy, which we estimate would destroy 22% of the enterprise value. The big winners of the plan were the bondholders of the three former investment banks and Citigroup, while the losers were JP Morgan shareholders and the US taxpayers.

Shocks to equity options' implied volatility are followed by persistently lower short-term rates. Shocks to puts' over calls' out-of-the-money implied volatilities (P/C) are followed by persistently higher rates. Stock and Treasury bond implied volatilities, which measure market and policy uncertainty, are countercyclical, while P/C, which measures downside risk, is procyclical. An equilibrium model in which investors and the central bank learn about composite regimes of economic and policy variables explains these dynamics, linking them to a learning-based, forward-looking Taylor rule. Survey data support our model's predictions on the effect of uncertainty on the level and fluctuations of implied volatilities.

We develop a general equilibrium model in which stock prices of innovative firms exhibit “bubbles” during technological revolutions. In the model, the average productivity of a new technology is uncertain and subject to learning. During technological revolutions, the nature of this uncertainty changes from idiosyncratic to systematic. The resulting bubbles in stock prices are observable ex post but unpredictable ex ante, and they are most pronounced for technologies characterized by high uncertainty and fast adoption. We find empirical support for the model's predictions in 1830–1861 and 1992–2005 when the railroad and Internet technologies spread in the United States.

Motivated by the recent rise of populism in Western democracies, we develop a tractable equilibrium model in which a populist backlash emerges endogenously in a strong economy. In the model, voters dislike inequality, especially the high consumption of “elites.” Economic growth exacerbates inequality due to heterogeneity in preferences , which leads to heterogeneity in returns on capital. In response to rising inequality, voters optimally elect a populist promising to end globalization. Equality is a luxury good. Countries with more inequality, higher financial development, and trade deficits are more vulnerable to populism, both in the model and in the data.

We argue that the number of firms going public changes over time in response to time variation in market conditions. We develop a model of optimal initial public offering (IPO) timing in which IPO waves are caused by declines in expected market return, increases in expected aggregate profitability, or increases in prior uncertainty about the average future profitability of IPOs. We test and find support for the model's empirical predictions. For example, we find that IPO waves tend to be preceded by high market returns and followed by low market returns.

We develop a model of political cycles driven by time-varying risk aversion. Agents choose to work in the public or private sector and to vote Democrat or Republican. In equilibrium, when risk aversion is high, agents elect Democrats-the party promising more redistribution. The model predicts higher average stock market returns under Democratic presidencies, explaining the well-known "presidential puzzle." The model can also explain why economic growth has been faster under Democratic presidencies. In the data, Democratic voters are more risk-averse and risk aversion declines during Democratic presidencies. Public workers vote Democrat while entrepreneurs vote Republican, as the model predicts.