Research:

Here is some of my current research. Feel free to send me an email (fbelo _at_ umn.edu) for a pdf copy of any of the current working papers. Comments are always welcome!


Working Papers:

"A Pure Production-Based Asset Pricing Model", (This version: April 2009) (Conditionally accepted at the Journal of Monetary Economics)

[This paper is based on my PhD dissertation at the University of Chicago (Thesis advisors: John Cochrane (chair), John Heaton, Monika Piazzesi and Pietro Veronesi]

A stochastic discount factor for asset returns is recovered from equilibrium marginal rates of transformation of output across states of nature, inferred from the producers' first order conditions. The marginal rate of transformation implies a novel macro-factor asset pricing model that does a reasonable job explaining the cross section of stock returns with plausible parameter values. Using a flexible representation of the firms' production technology, the producers' ability to transform output across states of nature is estimated to be high, in contrast with what is typically assumed in standard aggregate representations of the firms' production technology.

 

 

"Labor Hiring, Investment and Stock Return Predictability in the Cross Section"  (This version: May 2009) (with Santiago Bazdrech and Xiaoji Lin)

 

We show that firms with lower labor hiring and investment rates have on average higher future stock returns in the cross-section of US publicly traded firms. The predictability holds even after controlling for other known stock return predictors, varies across firms' technologies and exhibits a clear trend over time. We propose a production-based asset pricing model with adjustment costs in both labor and capital inputs to explain the empirical findings. Labor adjustment costs make hiring decisions forward looking. Convex adjustment costs imply that the returns of firms that are investing or hiring relatively less fluctuate more closely with economic conditions. Thus the firms' labor hiring and investment rates predict stock returns in the data because these variables proxy for the firms' time-varying conditional beta.

 

 

“A Labor-Augmented Investment-Based Asset Pricing Model” (with Xue Chen and Lu Zhang) (This version: Sep 2009)

 

We introduce labor adjustment costs in the q-theory model of expected returns and test the labor-augmented model using moments of the cross-section of expected stock returns as well as stock valuation ratios. Adding labor substantially reduces the pricing errors of the baseline q-theory model across portfolios sorted on investment-to-assets, book-to-market, asset growth, and labor hiring. The labor-augmented model also substantially outperforms the baseline model in explaining the cross-section of stock valuation ratios, especially across investment-to-assets portfolios. However, neither model can fully capture the large spread in the valuation ratio observed in the data, especially across the book-to-market portfolios.

 

“Is Investment in Public Capital Good News for the Stock Market?’’ (with Jianfeng Yu) (This version: Nov 2009)

 

We introduce public sector physical capital (e.g. highways) into the q-theory model of stock returns and test its implications for stock market return predictability in the US\ economy. If public capital increases the productivity of private inputs, high rates of investment in public capital forecast high future stock returns. We find empirical support for this prediction in both aggregate level and industry level data using long-horizon predictability regressions that control for the aggregate private investment rate and for other stock return predictors. We also find that the effect of public capital on stock returns varies substantially across industries and over time. The empirical findings suggest that public capital has a significant impact on firms' productivity.

 

 

“Government Spending, Political Cycles and the Cross Section of Stock Returns” (with Vito Gala and Jun Li) (This version: Aug 2009)

 

Using data from the Benchmark Input-Output Accounts of the National Income and Product Accounts, we construct a novel measure of industry's exposure to the government sector. We document that firms with different exposure earn on average different stock returns depending on the presidential partisan cycle. During Democratic presidential terms, firms with high government exposure earn on average higher stock returns than firms with low government exposure. The reverse holds true during Republican presidential terms. A long-short cross-sectional investment strategy that exploits the presidential partisan cycle predictability generates large excess returns of about 5% per year. The returns of this investment strategy cannot be explained by risk exposure to standard risk factors as captured by the unconditional and conditional version of the CAPM and by the Fama and French (1993) three factors asset pricing models.

 

 “Asset Pricing Implications of Alternative Macroeconomic Models of Inventory Investment” (with Xiaoji Lin) (This version: Nov 2009)

We show the firm level physical capital investment and inventory investment rates jointly predicts stock returns in the cross-section of US publicly traded firms. A long-short portfolio using physical capital and inventory investment information generates significant excess returns of about 8% per year. We use this empirical fact to distinguish between alternative macroeconomic models of inventory investment. Among the class of models considered here, we show that a model with stock out costs as well as adjustment costs in both physical capital and inventory is the most successful in matching the real quantities side facts in the data, consistent with Kahn and Thomas (2007). None of the models examined here, however, can match the empirical asset pricing facts.

 


Work in Progress:

"Government Size and Asset Prices" (with Antonio Mele)

TBA

 

"An Argument for Poor International Risk Sharing" (with Bob Goldstein and Jianfeng Yu)

 

TBA

 

 

"A Joint Estimation of Conditional Structural Models and Factor Models" (with Jeremy Graveline, Bob Goldstein and Fan Yang)

 

TBA

 


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