Browsing by Author "Xu, Yi (Daniel)"

The aim of this dissertation is to examine, model and estimate firm responses to

demand shocks by focusing on specific industries where demand shocks are well

identified. Combining reduced-form evidence and structural analysis, this dissertation

extends the economic literature by focusing on within-firm responses of firms

to two important demand shocks that are identifiable in empirical settings. First,

I focus on how firms respond to a decrease in effective demand due to competition

shocks coming from globalization. By considering China's accession to the World

Trade Organization in 2001 and its impact on the apparel industry, the aim of these

chapters is to answer how firms react to the increase in Chinese import competition,

what is the mechanism behind these responses, and how important they are in explaining

the survival of the Peruvian apparel industry. Second, I study how suppliers'

survival probability relates to the sudden disruption of their main customer-supplier

relationships with downstream manufacturers, conditional on suppliers' own idiosyncratic

characteristics such as physical productivity.

This dissertation consists of three essays in macroeconomics and firm dynamics. In the first essay, I study the role of ownership structure on firm-level hiring rules by investigating how firms make employment decisions focusing on those who belong to business groups. To do that end, I use the confidential Korean firm-level data and document novel empirical facts about the employment behavior of firms who belong to business groups in Korea, also known as Chaebol, which is significantly different from non-group firms and provide empirical and theoretical explanations for these new facts. I show that these facts are related to the group-level employment policy based on spillover effects and heterogeneous roles by business groups. In the second essay, I use Korean plant-level data in Korea and study productivity slowdown after the Global Financial Crisis of 2007-08. Applying the dynamic Olley/Pake productivity decomposition method, I find that decrease in allocative efficiency among continuing firms accounts for the collapse of productivity growth in the post-crisis period (2010-2015) by about 80$\%$. Another novel empirical finding is that big and the most productive firms contribute to the productivity slowdown the most while their market shares are not adjusted accordingly. Finally, in my last essay, I investigate macroeconomic implications of financial frictions in an economy where a market structure is endogenously determined. To that end, I develop a model of heterogeneous firms that face the linear demand system, generating a distribution of endogenous markups. The model predicts a negative selection effect of misallocation due to financial frictions by allowing unproductive firms to operate when the degree of competition is endogenously determined through the distribution of markups. This suggests an important role of the endogenous market structure in amplifying misallocation effects due to financial frictions.

The dissertation consists of three chapters relating to drug development and marketing strategies. Chapter 1 studies strategic direct-to-consumer and direct-to-physician advertising in the pharmaceutical industry. Chapter 2 examines the strategic interaction between government agencies in funding support for medical research. Chapter 3 investigates how pharmaceutical companies make R&D decisions for neglected diseases.

The first chapter studies how pharmaceutical companies make marketing strategies. It is well known that drug manufacturers invest heavily in advertising prescription drugs, but little is known about synergies between different advertising types. Furthermore, little is known about how patients and physicians respond differentially to advertising. Estimating causal relationship is challenging because advertising is not randomly assigned. Because the segmentation of television and radio markets are discrete and exogenous, comparing advertising efforts and demand across borders helps identify causal effects. Using data from 2008-2009 on anti-cholesterol markets and the border strategy, I find that a 10% increase in direct-to-consumer advertising per capita induces 0.3%-0.4% more detailing visits or 1% more detailing time for a given product in a given market. By further constructing and estimating a demand model that separately models physicians' and patients' decisions, I find that advertising to consumers induces more doctor visits. In addition, conditioning on visiting a doctor, advertising to consumers increases the number of requests for the advertised brand from patients with private insurance plans. Finally, after controlling for the patient request, direct-to-physician advertising increases the number of prescriptions for the promoted product.

How do governments respond to other governments when providing a global public good? Using data from 2007-2014 on medical research funding for infectious and parasitic diseases, we examine how governments and foundations in 41 countries respond to funding changes by the US government (which accounts for half of the funding for these diseases). Because funding across governments might be positively correlated due to unobserved drivers they have in common, we use variation in the representation of research-intensive universities on US Congressional appropriations committees as an instrument for US funding. We find that a 10 percent increase in US government funding for a disease is associated with a 2 to 3 percent reduction in funding for that disease by another government in the following year.

Companies increasingly engage in corporate social initiatives, but little is known about who cares and why. We measure corporate social initiatives as developing drugs for neglected diseases endemic in poor countries and charging low prices for all drugs (including heart disease and diabetes) for people in poor countries. These activities are costly, unlikely to be directly profitable, and can help millions of people. We find that companies most amenable to social initiatives are those with connections to the patients or the disease areas. We find that a company develops more treatments for neglected diseases if its headquarters is in a country with former colonies where the diseases create the largest burden. For example, Belgium, Britain, and France have former colonies in which diseases of poverty are prevalent, and companies based in Belgium, Britain, and France conduct more clinical trials for those diseases. Furthermore, companies based in countries with stronger colonial ties charge lower prices for all of their drugs in developing countries, including drugs for heart disease and diabetes. Finally, we show that these initiatives are unprofitable, unlike other forms of corporate social responsibility, such as environmental efforts, that can reduce costs and improve efficiency.

The dissertation consists of three chapters related to the low-price guarantee marketing strategy and energy efficiency analysis. The low-price guarantee is a marketing strategy in which firms promise to charge consumers the lowest price among their competitors. Chapter 1 addresses the research question "Does a Low-Price Guarantee Induce Lower Prices'' by looking into the retail gasoline industry in Quebec where there was a major branded firm which started a low-price guarantee back in 1996. Chapter 2 does a consumer welfare analysis of low-price guarantees to drive police indications and offers a new explanation of the firms' incentives to adopt a low-price guarantee. Chapter 3 develops the energy performance indicators (EPIs) to measure energy efficiency of the manufacturing plants in pulp, paper and paperboard industry.

Chapter 1 revisits the traditional view that a low-price guarantee results in higher prices by facilitating collusion. Using accurate market definitions and station-level data from the retail gasoline industry in Quebec, I conducted a descriptive analysis based on stations and price zones to compare the price and sales movement before and after the guarantee was adopted. I find that, contrary to the traditional view, the stores that offered the guarantee significantly decreased their prices and increased their sales. I also build a difference-in-difference model to quantify the decrease in posted price of the stores that offered the guarantee to be 0.7 cents per liter. While this change is significant, I do not find the response in comeptitors' prices to be significant. The sales of the stores that offered the guarantee increased significantly while the competitors' sales decreased significantly. However, the significance vanishes if I use the station clustered standard errors. Comparing my observations and the predictions of different theories of modeling low-price guarantees, I conclude the empirical evidence here supports that the low-price guarantee is a simple commitment device and induces lower prices.

Chapter 2 conducts a consumer welfare analysis of low-price guarantees to address the antitrust concerns and potential regulations from the government; explains the firms' potential incentives to adopt a low-price guarantee. Using station-level data from the retail gasoline industry in Quebec, I estimated consumers' demand of gasoline by a structural model with spatial competition incorporating the low-price guarantee as a commitment device, which allows firms to pre-commit to charge the lowest price among their competitors. The counterfactual analysis under the Bertrand competition setting shows that the stores that offered the guarantee attracted a lot more consumers and decreased their posted price by 0.6 cents per liter. Although the matching stores suffered a decrease in profits from gasoline sales, they are incentivized to adopt the low-price guarantee to attract more consumers to visit the store likely increasing profits at attached convenience stores. Firms have strong incentives to adopt a low-price guarantee on the product that their consumers are most price-sensitive about, while earning a profit from the products that are not covered in the guarantee. I estimate that consumers earn about 0.3% more surplus when the low-price guarantee is in place, which suggests that the authorities should not be concerned and regulate low-price guarantees. In Appendix B, I also propose an empirical model to look into how low-price guarantees would change consumer search behavior and whether consumer search plays an important role in estimating consumer surplus accurately.

Chapter 3, joint with Gale Boyd, describes work with the pulp, paper, and paperboard (PP&PB) industry to provide a plant-level indicator of energy efficiency for facilities that produce various types of paper products in the United States. Organizations that implement strategic energy management programs undertake a set of activities that, if carried out properly, have the potential to deliver sustained energy savings. Energy performance benchmarking is a key activity of strategic energy management and one way to enable companies to set energy efficiency targets for manufacturing facilities. The opportunity to assess plant energy performance through a comparison with similar plants in its industry is a highly desirable and strategic method of benchmarking for industrial energy managers. However, access to energy performance data for conducting industry benchmarking is usually unavailable to most industrial energy managers. The U.S. Environmental Protection Agency (EPA), through its ENERGY STAR program, seeks to overcome this barrier through the development of manufacturing sector-based plant energy performance indicators (EPIs) that encourage U.S. industries to use energy more efficiently. In the development of the energy performance indicator tools, consideration is given to the role that performance-based indicators play in motivating change; the steps necessary for indicator development, from interacting with an industry in securing adequate data for the indicator; and actual application and use of an indicator when complete. How indicators are employed in EPA’s efforts to encourage industries to voluntarily improve their use of energy is discussed as well. The chapter describes the data and statistical methods used to construct the EPI for plants within selected segments of the pulp, paper, and paperboard industry: specifically pulp mills and integrated paper & paperboard mills. The individual equations are presented, as are the instructions for using those equations as implemented in an associated Microsoft Excel-based spreadsheet tool.

U.S. MNEs are dominant producers in the economy, yet they invest considerably less and exhibit lower Tobin's q than domestic firms. Counterintuitively, the MNE investment premium mainly realizes as multinationalizing firms sharply reduce investment despite the productivity increase. The first chapter documents this novel fact and explains why MNEs invest less despite higher productivity as a consequence of multinationalization option exercise. Average U.S. public firms hold multinational investment opportunities as large as 40% of assets at the time of multinationalization. The model generates endogenous multinationalization by more productive firms and isolates the pure real option effect that explains MNE investment premium. Investment regressions ignoring commonly priced large-scale options such as multinationalization mistakenly suggests secular underinvestment for the most productive group of firms. Multinationalization is a common, large, and permanent corporate investment mechanism, and multinational status places one of the most informative observable for the optimal investment policy.

Domestic firms become considerably different in many aspects (e.g. size, profitability, and investment) as they transition to be multinational enterprises. The second chapter documents that multiple dimensional shifts of multinationalization dynamics spilling over to the aggregate realm as a large mass of U.S. firms multinationalized in the late-1990s. The mass-multinationalization hypothesis jointly explains recently raised pressing puzzles of aggregate movements of investment, q, and profitability while remaining consistent with the documented secular agglomeration patterns. Evidence also shows that multinationalization may further explain the dynamics of intangible, labor, and capital shares of production, increasing concentration, and market power. Mass-multinationalization of the late-1990s transmitted large firm-level dynamics of multinationalization events to the aggregate-level. The mass-multinationalization looks to be triggered by a substantial improvement in the incentive to integrate foreign demand chain for the U.S. products and services, rather than foreign supply chains which grew during the mid-2000s. The mass-multinationalization hypothesis is a firm-level and action-based mechanism that rationalizes the joint dynamics of secular movements without alternative explanations suggested in the literature.

My dissertation explores the implications of strategic investment on market structure,

new firm entry and technology diffusion. In particular, I build on existing

theoretical models and empirical methods and develop new ones to identify strategic

investment and empirically measure its implications. This dissertation aims to

provide a framework of how firms strategically invest to deter entry and what is the

optimal entry policy in these markets. Although there is a significant theoretical

literature on strategic investment, there is only limited empirical work.

In the first chapter of my dissertation, I present a simple theoretical model of

technology adoption to illustrate why firms may have incentive to excessively invest

in the case of entry threat.

In the second chapter of my dissertation, I present a model of strategic entry

deterrence and study how internet service providers’ interactions affect their technology

deployment at local markets. The goal is to capture an important trade-off:

cable firms adopt a new cable system to provide higher speeds, but the adoption

has a preemptive effect on fiber firms’ entry. I collect and combine unique firm-level

data on broadband technology deployment and exogenous city-firm level franchise

agreements data for potential fiber entrants for New York State. I provide evidence

of strategic investment by cable incumbents to deter fiber entry. Counterfactual scenarios

suggest that the industry has experienced 16% excessive investment in cable

adoption and 12% underinvestment in fiber entry both of which are explained by

these deterrence strategies. In addition, subsidies to cable incumbents in small markets

reduce fiber entry rate by 50%. I also find that policies that promote statewide

entry as opposed to existing subsidy programs mitigate the effects from these deterrence

strategies and increase fiber entry rate by 30%. These results have wide

implications for technology diffusion, quality provision and optimal subsidy policy

in markets under entry threat.

In the third chapter of my dissertation, I investigate the effect of entry barriers

for municipal providers on incumbents’ strategic investment in the US broadband

industry. I use a spatial regression discontinuity design by examining incumbents

strategic behavior across the exogenous entry barriers. I collect and combine unique

firm-level data on incumbents’ investment decisions and state-level data about legal

entry barriers. I find that technology diffusion is slower and internet service quality

is lower in markets with entry barriers. In particular, I find that entry threat leads

to an increased cable investment of 10%. This article contributes to the limited

empirical literature that uses quasi-experimental methods to identify firms’ strategic

behavior and the role of entry barriers in equilibrium product quality. In addition,

it contibutes to the literature that examines the effect of competition, entry barriers

and entry threat on technology adoption as well as the role of public investment.

I study the industrial organization of both online and offline retail markets, trying to uncover the impact of recent trends in this industry, namely store brand and big data. Chapter 2 gives a detailed discussion about the data collection and analysis process in both online and offline retail markets. I first describe two offline retailer scanner datasets provided by Nielsen, the Homescan dataset and the Retail Scan dataset. The former documents household shopping trips, and the latter provides detailed information of how many of each product are sold in every retailer. Then I move on to describe the datasets collected at a big Chinese e-commerce platform. I will talk about what the datasets look like, how the datasets are collected and organized, and finally how they are analyzed.

Chapter 3 studies the welfare consequences of store brands in the offline retail market. I model the vertical relationship between retailers and manufacturers with a Nash-in-Nash bargaining model. I show that stronger preference for store brand has an ambiguous effect on the non-store brand prices, and that this effect is nonlinear: it is more negative when store brand has a smaller market share. Using Nelson Homescan data. I find a 1% increase in store brand's market share leads to a more than 0.5% decrease in non-store brand prices. This shows that in reality, the main impact of store brand is to help retailers gain better bargaining positions vis-a-vis suppliers. Furthermore, I also find the negative effect is larger in magnitude when the market share is smaller.

Chapter 4 studies the impact of market intelligence data on online retailer performance, product choice, and market outcomes. To do so, I exploit a unique setting in which an e-commerce platform provides its sellers with a market intelligence tool called “Market Insight.” First I find Market Insight helps online sellers choose better products and increases their sales. Second I show the current design of Market Insight benefits consumers and the platform, though providing ``too much" information through Market Insight could be harmful. Finally I solve for the platform-optimal design of Market Insight and show that the total sales revenue on the platform would increase 8% under this design, and consumer welfare will increase 0.8%. I also compare the platform-optimal design to the socially optimal design. They are very close to each other, showing in this case, the platform acts like a benevolent social planner.

Housing market is one of the most important markets in the U.S. It is widely held that heterogeneity in the housing market plays an important part in affecting housing prices. My dissertation contributes to the literature by exploring the role of household migration and heterogeneous participants in the housing market at both the macro level and micro level.

Chapter 2 studies why and how household migration could contribute to spillovers of local housing booms. The chapter builds a theoretical framework and captures a multi-market equilibrium with household migration. Using IRS migration data and Housing Price Index data from FHFA, the chapter establishes the existence and magnitude of housing boom spillover effects through migration. It is found that housing prices increase with the number of migrants, and would increase more if migrants are from booming places. An increase in the fraction of migration inflow from booming counties by 10 percentage points results in an increase in the annual change in housing prices by 1 percentage point. Furthermore, the magnitude of the housing boom spillover effects is 62 percent.

In Chapter 3, I explore the differences between out-of-state home buyers and in-state home buyers in housing transactions and also investigate whether buyers' individual characteristics such as income and wealth could play an important role in determining housing prices. The chapter uses novel housing transactions data sets from TMLS and individual characteristics data from InfoUSA. Existing literature believed that out-of-state buyers pay significant price premiums for similar homes because of higher search costs or information disadvantages. The chapter revisits previous conclusions and finds that out-of-state buyers don't pay higher prices. Rather, it is the income and wealth of buyers that matter in affecting the housing price premiums.

In Chapter 4, I focus on what listing price strategies sellers would take and how sellers' heterogeneous characteristics affect their pricing strategies. By using data from TMLS and InfoUSA, I find that sellers' moving distance could affect their motivations to sell. External movers have the tendency to underprice and set the listing price around 3 percent lower compared with internal movers. Furthermore, it is found that elder sellers tend to overprice when setting the initial list price to gain more bargaining power.