Emin M. Dinlersoz

Who Do Unions Target? Unionization Over the Life-Cycle of U.S. Businesses

What type of businesses do unions target for organizing? A dynamic model of the union organizing process is constructed to answer this question. A union monitors establishments in an industry to learn about their productivity and decides which ones to organize and when. An establishment becomes unionized if the union targets it for organizing and wins the union certification election. The model predicts two main selection effects: unions secure elections in larger and more productive establishments early in their life-cycles, and among the establishments that experience an election, unions are more likely to win in smaller and less productive ones. These predictions find support in union certification election data for 1977-2007 matched with data on establishment characteristics. Other empirical regularities pertaining to union organizing are also documented.

What Businesses Attract Unions? Unionization over the Life‐Cycle of U.S. Establishments

What types of businesses attract unions? The study develops a theory of union learning and organizing to provide an answer to this question. A union monitors the productivity of establishments in an industry and uses this information to decide which ones to organize. An establishment becomes unionized if the union wins a certification election, the outcome of which can be influenced by costly actions taken by the two parties. The model offers predictions on the nature of union selection, which are examined empirically. Data on union certification elections, matched with data on establishment characteristics, are used to explore where union activity is concentrated.

Measuring Early-Stage Business Formation

New businesses play an important role in overall economic activity. They account for a sizable share of job creation, and they provide a key source of innovation that contributes to overall productivity growth.

Does Higher Productivity Dispersion Imply Greater Misallocation?A Theoretical and Empirical Analysis

Recent research maintains that the observed variation in productivity within industries reflects resource misallocation and concludes that large GDP gains may be obtained from market-liberalizing polices. Our theoretical analysis examines the impact on productivity dispersion of reallocation frictions in the form of costs of entry, operation, and restructuring, and shows that reforms reducing these frictions may raise dispersion of productivity across firms. The model does not imply a negative relationship between aggregate productivity and productivity dispersion. Our empirical analysis focuses on episodes of liberalizing policy reforms in the U.S. and six East European transition economies. Deregulation of U.S. telecommunications equipment manufacturing is associated with increased, not reduced, productivity dispersion, and every transition economy in our sample shows a sharp rise in dispersion after liberalization. Productivity dispersion under central planning is similar to that in the U.S., and it rises faster in countries adopting faster paces of liberalization. Lagged productivity dispersion predicts higher future productivity growth. The analysis suggests there is no simple relationship between the policy environment and productivity dispersion.

Wage Dynamics along the Life-Cycle of Manufacturing Plants

This paper explores the evolution of average wage paid to employees along the life-cycle of a manufacturing plant in U.S. Average wage starts out low for a new plant and increases along with labor productivity, as the plant survives and ages. As a plant experiences productivity decline and approaches exit, average wage falls, but more slowly than it rises in the case of surviving new plants. Moreover, average wage declines slower than productivity does in failing plants, while it rises relatively faster as productivity increases in surviving new plants. These empirical regularities are studied in a dynamic model of labor quality and quantity choice by plants, where labor quality is reflected in wages. The model’s parameters are estimated to assess the costs a plant incurs as it alters its labor quality and quantity in response to changes in its productivity over its life-cycle.

Modeling Single Establishment Firm Returns to the 2007 Economic Census

The Economic Census is one of the most important activities that the U.S. Census Bureau performs. It is critical for updating firm ownership/structure and industry information for a large number of businesses in the Census Bureau’s Business Register, impacting most other economic programs. Also, it feeds into Bureau of Economic Analysis products, such as benchmark inputoutput accounts and Gross Domestic Product. The overall check-in rate for the 2007 Economic Census was just over 86%. Establishments owned by multi-location companies returned over 90% of their forms, as compared to the roughly two million single-establishment firms sampled in the Census that returned just over 80%. We model the check-in rate for single-establishment firms by using a large number of variables that might be correlated with whether or not a firm returns a form in the Economic Census. These variables are broadly categorized as the characteristics of firms, measures of external factors, and features of the survey design. We use the model for two purposes. First, by including many of the factors that may be correlated with returns we aim to focus limited advertising and outreach resources to low-return segments of the population. Second, we use the model to investigate the efficacy of an unplanned intervention expected to increase return rates: using certified mailing for one of the form follow-ups.

Information and Drug Prices: Evidence from the Medicare Discount Drug Card Program

In early 2004, the U.S. Government initiated the Medicare Discount Drug Card Program (MDDCP), which created a market for drug cards that allowed elderly and handicapped subscribers to obtain discounts on their prescription drug purchases. Pharmacy-level prices for many drugs were posted on the program website weekly from May 29, 2004 to December 31, 2005, as the largest undertaking in the history of government-sponsored information release began with the hope of promoting competition by facilitating access to prices. A large panel of pharmacy-level drug price data collected from the Medicare website indicates that there was significant and persistent dispersion in prices across cards throughout the program. Moreover, the time-path of prices was non-monotonic; the prices declined initially when consumers were choosing cards but rose later when subscribers were unable to switch from one card to another. In contrast, contemporaneous control prices from on-line drug retailers, which were unrelated to the program, rose steadily over time, indicating that MDDCP prices evolved in a way different from the general evolution of prices outside the program. In view of the fact that the program rules prevented consumers from changing their cards at will, the evolution of MDDCP prices is consistent with certain models of dynamic price competition with consumer switching costs, such as Klemperer’s (1987a,b). Estimates of potential savings from purchasing at program prices are also provided.