Using a unique nationally representative sample of U.S. establishements surveyed in 1993 and 1996, we examine the relationship between workplace innovations and establishment productivity and wages. We match plant level practices with plant level productivity and wage outcomes and estimate production functions and wage equation using both cross sectional and longitudinal data. We find a positive and significant relationship between the proportion of non-managers using computers and productivity of establishments. We find that firms that re-engineer their workplaces to incorporate more high performance practices experience higher productivity.
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Occupational Classifications: A Machine Learning Approach
August 2018
Working Paper Number:
CES-18-37
Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.
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THE RELATIONSHIPS AMONG ACQUIRING AND ACQUIRED FIRMS' PRODUCT LINES
September 1990
Working Paper Number:
CES-90-12
This study develops detailed information on the relationships among the activities of acquiring and acquired firms at and near the time of merger for a sample of 94 takeovers undertaken between 1977-1982. We focus on takeovers for two reasons. First, takeovers are an important and controversial phenomenon. Second, takeovers allow us to look at marginal changes, admittedly large ones, in the firm's boundaries. Thus, they provide a useful way of examining relationships among activities of the firm without having to go into great detail regarding the historical decisions that generated the firm's current structure. While the individual establishment is our basic data unit, in this study we aggregate the activities of the firm to the line of business (LOB) level. Each LOB of an acquired firm is classified as to its relationship horizontal, vertical (upstream or downstream), and conglomerate to the LOBs of the acquiring firm. Using these categorizations we aggregate the LOB-level information to the firm level to investigate the degree to which our sample of mergers is specialized to particular types of relationships. While we find a significant group of unspecialized takeovers, most appear to fit a specific category. We also look at the pattern of closed operations immediately following the takeover. Closings are generally concentrated in operations involving horizontal relationships. Finally, we consider the pattern of relationships between hostile and friendly takeovers and whether takeover premiums vary by type of merger. Merger premiums are not related to the type of relationship between the acquiring and acquired firm, but they are tied to whether the takeover is friendly or hostile.
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Large Plant Data in the LRD: Selection of a Sample for Estimation
March 1999
Working Paper Number:
CES-99-06
This paper describes preliminary work with the LRD during our tenure at the Census Bureau as participants in the ASA/NSF/Census Research Program. The objective of the work described here were two-fold. First, we wanted to examine the suitableness of these data for the calculation of plant-level productivity indexes, following procedures typically implemented with time series data. Second, we wanted to select a small number of 2-digit industry groups that would be well suited to the estimation of production functions and systems of factor share equations and factor demand forecasting equations with system-wide techniques. This description of our initial work may be useful to other researchers who are interested in the LRD for the analysis of productivity growth and/or the estimation of systems of factor equations, because the specific results reported in this memo suggest that the data are of good quality, or because the nature of the tasks undertaken provides insight into issues that arise in the analysis of longitudinal establishment data.
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Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics
February 2016
Working Paper Number:
CES-16-10
We describe and analyze a method that blends records from both observed and synthetic microdata into public-use tabulations on establishment statistics. The resulting tables use synthetic data only in potentially sensitive cells. We describe different algorithms, and present preliminary results when applied to the Census Bureau's Business Dynamics Statistics and Synthetic Longitudinal Business Database, highlighting accuracy and protection afforded by the method when compared to existing public-use tabulations (with suppressions).
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Using Worker Flows in the Analysis of the Firm
August 2003
Working Paper Number:
tp-2003-09
This paper uses a novel approach to measure firm entry and exit, mergers and
acquisition. It uses information about the flows of clusters of workers across business
units to identify longitudinal linkage relationships in longitudinal business data. These
longitudinal relationships may be the result of either administrative or economic changes
and we explore both types of newly identified longitudinal relationships. In particular,
we develop a set of criteria based on worker flows to identify changes in firm
relationships ? such as mergers and acquisitions, administrative identifier changes and
outsourcing. We demonstrate how this new data infrastructure and this cluster flow
methodology can be used to better differentiate true firm entry/exit and simple changes in
administrative identifiers. We explore the role of outsourcing in a variety of ways but in
particular the outsourcing of workers to the temporary help industry. While the primary
focus is on developing the data infrastructure and the methodology to identify and
interpret these clustered flows of workers, we conclude the paper with an analysis of the
impact of these changes on the earnings of workers.
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On Productivity and Plant Ownership Change: New Evidence From the LRD
November 1993
Working Paper Number:
CES-93-15
This paper investigates the questions of what type of establishment experiences ownership change, and how the transferred properties perform after acquisition. Are they the profitable operations suggested by Ravenscraft and Scherer (1986), or the poorly operating ones found by Lichtenberg and Siegel (1992)? Is the primary motive of ownership change the rehabilitation of low productivity plants as suggested by Lichtenberg and Siegel? Our empirical work is based on an unbalanced panel of 28,294 plants taken from the U.S. Bureau of the Census' Longitudinal Research Database ( LRD ). The data set provides complete coverage of the food manufacturing industry (SIC 20) for the period 1977-1987. Our principle findings are that (1) ownership change is generally associated with the transfer of plants with above average productivity, however, large plants, empirically, those with more than 200 employees, are more likely to be purchased than closed when they are performing poorly; and (2) transferred plants experience improvement in productivity performance following the ownership change.
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Productivity Adjustments and Learning-by-Doing as Human Capital
November 1997
Working Paper Number:
CES-97-17
This paper measures plant-level productivity gains associated with learning curves across the entire manufacturing sector. We measure these gains at plant startups and also after major employment changes. We find: 1.) The gains are strongly associated with a variety of human capital measures implying that learning-by-doing is largely a firm-specific human capital investment. 2.) This implicit investment is large; many plants invest as much in learning-by-doing as they invest in physical capital and much more than they invest in formal job training. 3.) This investment differs persistently over industries and is higher with greater R&D. 4.) Consistent with a learning-by-doing interpretation, the human capital investment is much larger following employment decreases than increases. We conclude that learning-by-doing is a major factor in wage determination, technical progress and asymmetric employment adjustment costs.
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A FIRST STEP TOWARDS A GERMAN SYNLBD: CONSTRUCTING A GERMAN LONGITUDINAL BUSINESS DATABASE
February 2014
Working Paper Number:
CES-14-13
One major criticism against the use of synthetic data has been that the efforts necessary to generate useful synthetic data are so in- tense that many statistical agencies cannot afford them. We argue many lessons in this evolving field have been learned in the early years of synthetic data generation, and can be used in the development of new synthetic data products, considerably reducing the required in- vestments. The final goal of the project described in this paper will be to evaluate whether synthetic data algorithms developed in the U.S. to generate a synthetic version of the Longitudinal Business Database (LBD) can easily be transferred to generate a similar data product for other countries. We construct a German data product with infor- mation comparable to the LBD - the German Longitudinal Business Database (GLBD) - that is generated from different administrative sources at the Institute for Employment Research, Germany. In a fu- ture step, the algorithms developed for the synthesis of the LBD will be applied to the GLBD. Extensive evaluations will illustrate whether the algorithms provide useful synthetic data without further adjustment. The ultimate goal of the project is to provide access to multiple synthetic datasets similar to the SynLBD at Cornell to enable comparative studies between countries. The Synthetic GLBD is a first step towards that goal.
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Evolving Property Rights and Shifting Organizational Forms: Evidence From Joint-Venture Buyouts Following China's WTO Accession
March 2013
Working Paper Number:
CES-13-05
China's WTO accession offers a rare opportunity to observe multinationals' response to changes in property rights in a developing country. WTO accession reduced incentives for joint ventures while reducing constraints on wholly owned foreign subsidiaries. Concomitant with these changes was a more liberal investment environment for indigenous investors. An adaptation of Feenstra and Hanson's (2005) property rights model suggests that higher the productivity and value added of the joint venture, but the lower its domestic sales share, the more likely the venture is to be become wholly foreign owned following liberalization. Theory also suggests that an enterprise with lower productivity but higher value added and domestic sales will be more likely to switch from a joint venture to wholly domestic owned. Using newly created enterprise-level panel data on equity joint ventures and changes in registration type following China's WTO accession, we find evidence consistent with the property rights theory. More highly productive firms with higher value added and lower domestic sales shares are more likely to become wholly foreign owned, while less productive firms focused on the Chinese market are more likely to become wholly domestic owned rather than remain joint ventures. In addition to highlighting the importance of incomplete contracts and property rights in the international organization of production, these results support the view that external commitment to liberalization through WTO accession influences multinational and indigenous firms' behavior.
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The Effects of Industry Classification Changes on US Employment Composition
June 2018
Working Paper Number:
CES-18-28
This paper documents the extent to which compositional changes in US employment from 1976 to 2009 are due to changes in the industry classification scheme used to categorize economic
activity. In 1997, US statistical agencies began implementation of a change from the Standard Industrial Classification System (SIC) to the North American Industrial Classification System (NAICS). NAICS was designed to provide a consistent classification scheme that consolidated declining or obsolete industries and added categories for new industries. Under NAICS, many activities previously classified as Manufacturing, Wholesale Trade, or Retail Trade were re-classified into the Services sector. This re-classification resulted in a significant shift of measured activities across sectors without any change in underlying economic activity. Using a newly developed establishment-level database of employment activity that is consistently classified on a NAICS basis, this paper shows that the change from SIC to NAICS increased the share of Services employment by approximately 36 percent. 7.6 percent of US manufacturing employment, equal to approximately 1.4 million jobs, was reclassified to services. Retail trade and wholesale trade also experienced a significant reclassification of activities in the transition.
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