Research Database

In social science research, household income is widely used as a stand-in for, or approximation to, the economic well-being of households. In a parallel way, income-inequality has been employed as a stand-in for inequality of economic well-being, or for brevity, "economic-inequality." But there is a force in market economies, ones with extensive amounts of monopoly, like the United States, which leads income-inequality to understate economic-inequality. This force has not been recognized before and derives from how monopolies behave. Monopolies, of course, raise prices. This reduces the purchasing power of households, or the value of their income. But monopolies, in fact, reduce the purchasing power of low-income households much more than high-income households. What has not been recognized is that, in many markets, as monopolies raise the prices for their goods, they simultaneously destroy substitutes for their products, low-cost substitutes that are purchased by low-income households. In these markets, then, while high-income households face higher prices, low-income households are shut out of markets, markets for goods and services that are extremely important for their economic well-being. It often leaves them with extremely poor alternatives, and sometimes none, for these products. Some of the markets we discuss include those for housing, financial services, and K-12 public education services. We also discuss markets for legal services, health care services, used durable equipment and repair services. Monopolies that infiltrate public institutions to enrich members, including those in foster care services, voting institutions and antitrust institutions, are also discussed.

U.S. government concerns about great disparities in housing conditions are at least 100 years old. For the first 50 years of this period, U.S. housing crises were widely considered to stem from the failure of the construction industry to adopt new technology -- in particular, factory production methods. The introduction of these methods in many industries had already greatly narrowed the quality of goods consumed by low- and high-income Americans. It was widely known why the industry failed to adopt these methods: Monopolies in traditional construction blocked and sabotaged them. Very little has changed in the last 50 years. The industry still fails to adopt factory methods, with monopolies, like HUD and NAHB, blocking attempts to adopt them. As a result, the productivity record of the construction industry has been horrendous. One thing has changed. Today there is very little discussion of factory-built housing; of the very few that recognize the industry's failure to adopt factory methods, there is no realization that monopolies are blocking the methods. That these monopolies, in particular, HUD and NAHB, can cause so much hardship in our country, and through misinformation and deceit cover it up, seems almost beyond belief. But, unfortunately, it's a history that is not uncommon. There are many other industries where monopolies have inflicted great harm on Americans, like the tobacco industry, yet through misinformation and deceit cover up the great harm.

Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.

The Covid-19 crisis has exposed the vast inequalities that exist within the US economy. As the virus has spread silently, it has laid bare other crises that face our nation---especially the economic vulnerabilities of the country's poor and marginalized. Many of these vulnerabilities can, in fact, be traced back to a single cause that itself has spread silently, but over the last several decades, not months: Monopolies. That monopolies are "silent spreaders of poverty and economic inequality" was well known to economic and legal scholars of the 1930s and 1940s. Wendell Berge, who was Assistant Attorney General for Antitrust in the 1940s, wrote: "Monopoly conditions have often grown up almost unnoticed by the public until one day it is suddenly realized that an industry is no longer competitive but is governed by an economic oligarchy." The harm caused by these monopolies that have mostly avoided detection often exist in markets with small firms, low concentration levels, and small price-cost margins, as in residential construction, or wreak their harm in public institutions, where prices and concentration have no meaning. While there has been a very welcome resurgence in the concern about monopolies in the last decade or so, this has primarily involved vast corporations, and often about their threat to democratic institutions. Though greatly welcomed, we should not let apprehension with these larger companies distract us from the many hidden monopolies that have silently spread harm to the poor for the last 100 years -- not just the last 10 or so. We should stand on the shoulders of giants that taught us this about monopolies, not only Berge, but Thurman Arnold, Henry Simons, and others.

Today, monopolies inflict great harm on low- and middle-income Americans. One particularly pernicious way they harm them is by sabotaging low-cost products that are substitutes for the monopoly products. I'll argue that the U.S. housing crisis, legal crisis, and oral health crisis facing the low- and middle-income Americans are, in large part, the result of monopolies destroying low-cost alternatives in these industries that the poor would purchase. These results would not surprise those studying monopolies in the first half of the 20th century. During this period extensive evidence was developed showing monopolies engaging in these same activities and many others that harmed the poor. Models of monopoly were constructed by giants in economics and law, such as Henry Simons and Thurman Arnold, to explain these impacts of monopoly. These models are of sabotaging monopolies. Unfortunately, in the 1950s, the economics profession turned its back on this evidence, these models and these giants. It embraced the Cournot model of monopoly, that found in textbooks today. In this model the monopolist chooses its price, nothing more. Gone are the decisions on whether to sabotage substitutes or to employ any of the other weapons at the disposal of sabotaging monopolies. I'll call this Cournot monopoly the toothless monopoly. Using this model, the economics profession has concluded that the costs of monopoly are small. But the toothless monopoly model is ill-equipped to study the "costs of monopoly." By relying on it, the economics profession has made major errors in its study of monopoly.

This paper develops and structurally estimates a labor market model that integrates job assignment, learning, and human capital acquisition to account for the main patterns of careers in firms. A key innovation is that the model incorporates workers’ job mobility within and between firms, and the possibility that, through job assignment, firms affect the rate at which they acquire information about workers. The model is estimated using longitudinal administrative data on managers from one U.S. firm in a service industry (the data of Baker, Gibbs, and Holmström (1994a,b)) and fits the data remarkably well. The estimated model is used to assess both the direct effect of learning on wages and its indirect effect through its impact on the dynamics of job assignment. Consistent with the evidence in the literature on comparative advantage and learning, the estimated direct effect of learning on wages is found to be small. Unlike in previous work, by jointly estimating the dynamics of beliefs, jobs, and wages imposing all of the model restrictions, the impact of learning on job assignment can be uncovered and the indirect effect of learning on wages explicitly assessed. The key finding of the paper is that the indirect effect of learning on wages is substantial: overall learning accounts for one quarter of the cumulative wage growth on the job during the first seven years of tenure. Nearly all of the remaining growth is from human capital acquisition. A related novel finding is that the experimentation component of learning is a primary determinant of the timing of promotions and wage increases. Along with persistent uncertainty about ability, experimentation is responsible for substantially compressing wage growth at low tenures.

In this appendix I present details of the model and the empirical analysis, and results of counterfactual experiments omitted from the paper. In Section 1 I describe a simple example that illustrates how, even in the absence of human capital acquisition, productivity shocks, or separation shocks, the learning component of the model can naturally generate mobility between jobs within a firm and turnover between firms. I also include the proofs of Propositions 1 and 2 in the paper. In Section 2 I discuss model identification in detail, where, in particular, I prove that information in my data on the performance ratings of managers allows me to identify the learning process separately from the human capital process. In Section 3 I describe the original U.S. firm dataset of Baker, Gibbs, and Holmström (1994a,b), on which my work is based. In Section 4 I provide details about the estimation of the model, including the derivation of the likelihood function, a description of the numerical solution of the model, and a discussion of the results from a Monte Carlo exercise showing the identifiability of the model’s parameters in practice. There I also derive bounds on the informativeness of the jobs of the competitors of the firm in my data, based on the estimates of the parameters reported in the paper. Finally, in Section 5 I present estimation results based on a larger sample that includes entrants into the firm at levels higher than Level 1. Results of counterfactual experiments omitted from the paper are contained in Tables A.12–A.14.