کلان داده ها در امور مالی و رشد شرکت های بزرگ Big data in finance and the growth of large firms

One of the main question in macroeconomics today is why small firms are being replaced with larger ones. Over the last three decades, the percentage of employment at firms with less than 100 employees has fallen from 40% to 35% (Figure 1a); the annual rate of new startups has decreased from 13% to less than 8%, and the share of employment at young firms (less than 5 years) has decreased from 18% to 8% (Davis and Haltiwanger, 2015). While small firms have struggled, large firms (more than 1000 employees) have thrived: The share of the U.S. labor force they employ has risen from one quarter in the 1980s, to about a third today. At the same time, the revenue share of the top 5% of firms increased from 57% to 67% (Figure 1b). Figure 1 about here. One important difference between large and small firms is their cost of capital (Cooley and Quadrini, 2001). Hennessy and Whited (2007) document that larger firms, with larger revenues, more stable revenue streams, and more collateralizable equipment, are less risky to creditors and thus pay lower risk premia. But this explanation for the trend in firm size is challenged by the fact that while small firms are more volatile, the volatility gap between small firms and large firms cash flows has not grown. 1 Alternative, the trend in covariance of firm stock prices with market portfolio, as measured by CAPM β, is not significantly different across firms of different sizes. If neither volatility nor covariance with market risk has diverged, how could risk premia and thus the cost of capital diverge? What introduces a wedge between unconditional vari35 ance or covariance and risk is information. Even if the payoff variance is constant, better information can make payoffs more predictable and therefore less uncertain.