Shihan Shen (沈诗涵)

Abstract:  This paper analyzes the quantitative contribution of capital-skill complementarity in accounting for rising wage inequality, as in Krusell, Ohanian, Rios-Rull, and Violante (KORV, 2000). We study how well the KORV framework accounts for more recent data, including the large changes in labor’s share of income that occurred after the KORV estimation period ended. We also study how using information and communications technology (ICT) capital as the complementary capital stock affects the model’s implications for inequality and overall model fit. We find significant evidence for continued capital-skill  complementarity across all model permutations we analyze. Despite nearly 30 years of additional data, we find very little change to the original KORV estimated substitution elasticity estimates when the total stock of capital equipment is used as the complementary capital stock. We find much more capital-skill complementarity when ICT capital is used. The KORV framework continues to closely account for rising wage inequality through 2019, though it misses the three-percentage point decline in labor’s share of income that has occurred since 2000.

Abstract:   A growing literature studies the recent business dynamism from a productivity-driven perspective. This paper takes a novel demand-driven view that not only explains the declining business dynamism but also addresses the well-documented cross-firm reallocation effects. The key driving force is the development of data technologies that improves the targeting accuracy of firm advertising investment. First, I empirically show that while digital technology improves all firms’ matching efficiency, it generates an advantage for firms with larger customer base which naturally provides more data records. Then, I develop a general equilibrium model with product market search frictions. The unequal matching rates of advertising imply a reduction of net inflow of customers for small firms and an increase of that for large firms compared to the pre-digital era. The rapid accumulation of customers and revenues in large firms crowds out small firms’ production and R&D investment. The calibrated model accounts for around 44% of the rise in industry concentration and 27% of productivity growth. Finally, I show that digital technologies improve the overall welfare, but still induces misallocation that assigns customers to large yet less productive firms more than optimal.

Presentations: Third DC Search and Matching Workshop, Macroeconomics Across Time and Space Conference Philadelphia, RISE Conference on Firms, Productivity, and Growth, West Coast Search-and-Matching workshop, ES Meetings (North America Summer, Asia), UNC-Chapel Hill (scheduled),  University of Houston, Wisconsin-Madison, Carnegie Mellon Tepper, Rice University, Peking University (CCER, Guanghua, HSBC), Tsinghua University, National University of Singapore (Econ, Finance), Singapore Management University, CUHK Shenzhen, 2022 EWMES (Scheduled), 2022 Trans-Atlantic Doctoral Conference (TADC),  2022 AFA Ph.D. poster session, 2021 Asian Econometric Society Meeting, 2021 China Meeting of the Econometric Society, UCLA proseminar

Abstract:    We study how central banks' purchase of corporate bonds affects bond markets and firm decisions on bond issuance. Using micro-level data, we find that the average maturity of newly issued bonds became longer during the COVID-19 pandemic after central banks started purchasing corporate bonds, which is contrary to the conventional wisdom that firms tend to choose shorter maturities in times of crisis. We develop a model featuring segmented over-the-counter secondary bond markets and firms' endogenous financing decisions. Firm's debt maturity choice depends on a trade-off between fixed issuance costs in the primary market and search frictions in the secondary market. Then we use the model to study the impact of central banks injecting liquidity through direct purchases of bonds in one of the segmented markets. Our model generates predictions that are consistent with the data --- central bank's participation improves market liquidity for both eligible and ineligible bonds, lowers interest rates on bond issuance, induces firms to opt for longer maturities and issue more debt. We further discuss the efficiency implications of such interventions.

Abstract:    "Big tech" companies dominate many industries and are very profitable, but they did not get there alone. In this paper, I develop a Schumpeterian growth model to study the macroeconomic implications of mergers and acquisitions, which is a key way for many incumbents to expand and gain profits. There are two types of acquisitions, defensive M&A in which incumbents buy out the rivals to eliminate competition, and expansionary M&A where the acquirer complements startups to do radical innovations to take over businesses from other firms. The relative gains of target firms in these two types of M&A influence startups' incentives to choose incremental or radical innovations, and thus affect aggregate productivity and social welfare. I use the model to show the effect on business dynamism of introducing a technological change that enables more firms to generate positive synergies in M&A. The surge of expansionary M&A by incumbent firms increases productivity at the beginning. However, as more and more industries are taken over by these firms, their high profits enable them to pay high prices in defensive M&A to startups doing incremental innovation. This explains the rise of M&A, the increase of average markup and concentration, and the slowdown of innovation and productivity.

Presentations: 2021 WEAI, UCLA proseminar

Abstract:   The compensation of corporate executives is governed by complex contracts that encourage them to partially internalize the effect of their supply decisions on competitors. Interlocking directorates incentivize softer competition among product market rivals, while relative performance evaluation (RPE) rewards managers for aggressive product market conduct (i.e. "crushing the competition"). These incentives create an intricate network of "friends" and "foes" relationships among corporations that distort prices and shape product market outcomes. In this study, we map this network comprehensively for the first time for the universe of US public firms, by processing and cleaning unstructured data from tens of thousands of executive compensation contracts. We then embed these incentives into a general equilibrium model of oligopoly with GHL demand and ultra-realistic managerial objectives. We use our model to quantify the influence of these incentives on individual firm supply decisions, markups, allocative efficiency, and consumer welfare.

Presentations: UChicago Stigler Center Affiliate Conference, SIOE

Abstract:   We leverage an extremely large digital database of news articles, containing 1.5 billion pieces of news from over 32,000 news sources, that have been tagged by topic and industry using artificial intelligence, to construct industry-level measure of firms' exposure to a variety of economic shocks. After showing how our measurement framework can be applied to study a multiplicity of shocks, ranging from the introduction of artificial intelligence to epidemics, we focus on a specific application. We use our database to study the causality of policy uncertainty on firm equity volatility and capital investment. We ask whether companies that operate in industries more exposed to regulations and policy shocks experience higher stock price volatility and whether they scale back capital investment in response to higher policy uncertainty. While existing data sources only allow to capture time-series variation in policy uncertainty, our data and methodology enable us to investigate the transmission of policy uncertainty shocks to firms on a cross-sectional basis; this can drastically improve our ability to identify the causal impact of policy uncertainty shocks.

Undergraduate level: Investments.  Spring 2024.

PhD level: Topics in Macroeconomics (second-year field course).  Spring 2014.

Macroeconomics Theory (Graduate level), TA for Prof. Lee Ohanian.   Fall 2019, Fall 2020.

Investments, TA for Prof. Pierre-Olivier Weill.   Winter 2021.

Finance, TA for Prof. Patrick Convery.   Fall 2021, Winter 2022.

Econometrics, TA for Prof. Rodrigo Pinto.   Fall 2018, Spring 2020.

Principles of Economics (Macro).   Spring 2019, Spring 2021.

Principles of Economics (Micro).   Winter 2019, Spring 2022.

Empirical Finance and Matlab Programming.  Fall 2015.

Options, Futures and Other Derivatives.  Spring 2015.