Browsing by Subject "superstar firms"

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    Essays in Macroeconomics and Labor Economics
    (2018-05) Diez Catalan, Luis
    This dissertation is composed of three chapters. Chapter 1 documents a divergence in the evolution of the labor share between services and non-services industries in the United States since 1980. Over this period, the labor share for services industries increased by an average of 6 percentage points, whereas for the rest of industries it decreased by an average of 14 percentage points. By exploiting industry-level data, I find that the divergence is occurring in the large majority of sub-industries, and is correlated with changes in labor intensity across sub-industries. In order to understand the underlying mechanisms behind this divergence, I build a quantitative two-sector model and show that the decline in the aggregate labor share and the divergence across industries are both consistent with the observed declining trend in the relative price of investment goods. Critically, differences in the substitutability between capital and labor, and differences in technical change across industries can account for the divergence. Chapter 2 (with Sergio Salgado) documents that part of the increase in top wealth inequality in the United States since the 1980s relates to the rise of ``superstar firms.'' We build a novel owner-firm matched panel dataset using information from the official records of the Securities and Exchange Commission, Forbes, and Compustat. Using this data we document that: (i) firms at the upper end of the market value distribution are disproportionately controlled by individuals at the top of the wealth distribution, (ii) these individuals invest a large fraction of their net worth in one or two main firms which we interpret as evidence of lack of asset diversification, and (iii) the output, employment, and market value shares accounted for by these firms has increased substantially over the last 30 years. Chapter 3 (with Simone Civale and Fatih Fazilet) develops and tests a discretization method to calibrate a Markov chain that features non-zero skewness and high kurtosis.
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    Essays on Firms, Finance, and Macroeconomy
    (2022-06) Su, Dan
    The primary goal of this dissertation is to understand how the business activities of companies impact the macroeconomy. More specifically, it contains three essays. In the first essay “Rise of Superstar Firms and Fall of the Price Mechanism”, I investigatethe misallocation implications of corporate internal financing. I introduce product market competition and corporate risk management into a standard continuous-time heterogeneous agent model with incomplete markets. I show that the economy’s ability to allocate resources across different agents through the price mechanism is bounded by corporate internal savings as there is no market to equalize the marginal value of internal resources across firms. In other words, corporate cash can help achieve dynamic efficiency across times at the firm level but not static efficiency across individuals at the macro level. More importantly, misallocation – defined as the static resource allocation efficiency across individuals – increases in the new economy where (superstar) firms rely more on internal financing due to the increased earnings risk. Finally, this model can quantitatively match the deteriorating capital allocation efficiency in the U.S. data. In the second essay “The Rise of (Mega-)Firms with Negative Net Earnings”, I document the prevalence of public companies with negative net earnings since the 1970s. The fraction of firms with negative net income has increased sharply from 18% in 1970 to 54% in 2019. Such an increase is mainly driven by the right shifts in the mean, i.e., the increasing popularity of sizable firms that are not profitable. Based on the existing literature on customer capital, I conjecture that the increasing returns-to-scale in the new economy is the main driver behind it. I provide three pieces of supporting evidence. First, earning losses mostly come from the growing customer capital expenses instead of production-related costs, capital investments, or R&D expenditures. Second, cross-sectionally, firms with higher markup tend to have lower net incomes. Third, industries with low marginal production costs, on average, have higher percentages of unprofitable companies. The last essay “The Macroeconomics of TechFin” is to investigate the business cycle implications of TechFin. Over the past few years, many large technology companies have started lending in the capital markets, i.e., “TechFin”. How should we modify our existing macro-finance theories to accommodate the rise of this new financial intermediary? In this paper, I introduce both a banking sector and a TechFin sector into a continuous-time general equilibrium model with heterogeneous entrepreneurs and incomplete markets. These two financial sectors are identical except for the types of borrowing constraints faced by entrepreneurs. Entrepreneurs borrowing from banks are subject to the standard collateral-based borrowing constraints. In contrast, technology advantages allow the big tech companies to resolve agency costs and perform cash flow-based lending. I use a deep learning neural network approach to obtain global solutions, and the main conclusions are twofold. First, this new TechFin credit system leads to a higher capital allocative efficiency in the steady state. Second, the existence of BigTech lending acts as a propagation mechanism and makes the economy sensitive to the second-moment uncertainty shocks: a small and transitory micro-uncertainty shock can lead to amplified and persistent changes in aggregate outputs. This new financialaccelerator mechanism, associated with the new TechFin sector, differs from the classic one (e.g. Bernanke and Gertler, 1989; Kiyotaki and Moore, 1997) in three aspects: micro uncertainty instead of aggregate productivity is the primitive shock; financial friction comes from earnings-based borrowing constraints instead of collateral-based ones; and the feedback loops happen between net worth inequality, instead of net worth level, and asset prices.