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I develop a new method that puts structure on financial market data to forecast economic outcomes. I apply it to study the IT sector's transition to its long-run share in the US economy, along with its implications for future growth. Future average annual productivity growth is predicted to fall to 52bps from the 87bps recorded over 1974-2012, due to intensifying IT sector competition and decreasing returns to employing IT. My median estimate indicates the transition ends in 2033. I estimate these numbers by building an asset pricing model that endogenously links economy-wide growth to IT sector innovation governed by the sector's market valuation, and by calibrating it to match historical data on factor shares, price-dividend ratios, growth rates, and discount rates. Consistent with this link, I show empirically that the IT sector's price-dividend ratio univariately explains nearly half of the variation in future productivity growth.
Persistent differences in interest rates across countries account for much of the profitability of currency carry trade strategies. The high-interest rate ``investment'' currencies tend to be ``commodity currencies,'' while low interest rate ``funding" currencies tend to belong to countries that export finished goods and import most of their commodities. We develop a general equilibrium model of commodity trade and currency pricing that generates this pattern via frictions in the shipping sector. The model predicts that commodity-producing countries are insulated from global productivity shocks by the limited shipping capacity, which forces the final goods producers to absorb the shocks. As a result, a commodity currency is risky as it tends to depreciate in bad times, yet has higher interest rates on average due to lower precautionary demand, compared to the final good producer. The model's predictions are strongly supported in the data. The commodity-currency carry trade explains a substantial portion of the carry-trade risk premia, and all of their pro-cyclical predictability with commodity prices and shipping costs, as predicted by the model.
This paper shows how non-linearities in returns induced by delisting events can affect the inference about the behavior of delisting stocks. Because these events are both extreme and introduce a floor on expected stock returns, the correct factor model is
likely to be quite non-linear. As a result the estimated alphas and loadings in standard linear models are biased. We show that although these biases can be significant for abnormal excess returns they are generally quite small for factor loadings. Empirically this is because delisting events are largely uncorrelated with systematic risk factors. After we correct these biases we see little evidence of underperformance for portfolios of distressed stocks.
We use the Merton (1974) model of capital structure to illustrate the intimate link between bond volatility and credit spreads. We then introduce a simple measure of bond volatility which alone captures 55.7% of variation in credit spreads in our sample, compared to 37.5% explained by a combination of five liquidity measures and 60.2% explained by an improved control for credit risk. Regressing spreads on our simple measure and our improved control for credit risk alone yields an adjusted R-squared of 69.8%; adding the liquidity measure only minimally augments the fit. We confirm the lack in explanatory power of the liquidity measure for subsamples of investment and speculative grade bond-quarters before, during and after the financial crisis. However, at the onset of the crisis we observe increases (decreases) in spreads of speculative (investment-) grade bonds with low pre-crisis trading activity, indicating price pressure caused by a flight to quality during the crisis. We conclude that while illiquid bonds can experience temporary price pressure in times of severe economic distress, bond spreads do not contain economically significant premia for contemporaneous illiquidity.