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Investigating the Effect of Innovation Activities of Firms on Innovation Performance: Does Firm Size Matter?
January 2025
Working Paper Number:
CES-25-04
Understanding the relationship between a firm's innovation activities and its performance has been of great interest to management scholars. While the literature on innovation activities is vast, there is a dearth of studies investigating the effect of key innovation activities of the firm on innovation outcomes in a single study, and whether their effects are dependent on the nature of firms, specifically firm size. Drawing from a longitudinal dataset from the Business Research & Development and Innovation Survey (BRDIS), and informed by contingency theory and resource orchestration theory, we examine the relationship between a firm's innovation activities - including its Research & Development (R&D) investment, securing patents, collaborative R&D, R&D toward new business areas, and grants for R&D - and its product innovation and process innovation. We also investigate whether these relationships are contingent on firm size. Consistent with contingency theory, we find a significant difference between large firms and small firms regarding how they enhance product innovation and process innovation. Large firms can improve product innovation by securing patents through applications and issuances, coupled with active participation in collaborative R&D efforts. Conversely, smaller firms concentrate their efforts on the number of patents applied for, directing R&D efforts toward new business areas, and often leveraging grants for R&D efforts. To achieve process innovation, a similar dichotomy emerges. Larger firms demonstrate a commitment to securing patents, engage in R&D efforts tailored to new business areas, and actively collaborate with external entities on R&D efforts. In contrast, smaller firms primarily focus on securing patents and channel their R&D efforts toward new business pursuits. This nuanced exploration highlights the varied strategies employed by large and small firms in navigating the intricate landscape of both product and process innovation. The results shed light on specific innovation activities as antecedents of innovation outcomes and demonstrate how the effectiveness of such assets is contingent upon firm size.
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The Role of R&D Factors in Economic Growth
November 2024
Working Paper Number:
CES-24-69
This paper studies factor usage in the R&D sector. I show that the usage of non-labor inputs in R&D is significant, and that their usage has grown much more rapidly than the R&D workforce. Using a standard growth decomposition applied to the aggregate idea production function, I estimate that at least 77% of idea growth since the early 1960s can be attributed to the growth of non-labor inputs in R&D. I demonstrate that a similar pattern would hold on the balanced growth path of a standard semi-endogenous growth model, and thus that the decomposition is not simply a by-product of rising research intensity. I then show that combining long-running differences in factor growth rates with non-unitary elasticities of substitution in idea production leads to a slowdown in idea growth whenever labor and capital are complementary. I conclude by estimating this elasticity of substitution and demonstrate that the results favor complimentarities.
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Grassroots Design Meets Grassroots Innovation: Rural Design Orientation and Firm Performance
March 2024
Working Paper Number:
CES-24-17
The study of grassroots design'applying structured, creative processes to the usability or aesthetics of a product without input from professional design consultancies'remains under investigated. If design comprises a mediation between people and technology whereby technologies are made more accessible or more likely to delight, then the process by which new grassroots inventions are transformed into innovations valued in markets cannot be fully understood. This paper uses U.S. data on the design orientation of respondents in the 2014 Rural Establishment Innovation Survey linked to longitudinal data on the same firms to examine the association between design, innovation, and employment and payroll growth. Findings from the research will inform questions to be investigated in the recently collected 2022 Annual Business Survey (ABS) that for the first time contains a Design module.
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Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry
April 2018
Working Paper Number:
CES-18-16
This paper addresses the relative effectiveness of market vs program based climate policies. We compute the carbon price resulting in an equivalent reduction in energy from programs that eliminate the efficiency gap. A reduced-form stochastic frontier energy demand analysis of plant level electricity and fuel data, from energy-intensive chemical sectors, jointly estimates the distribution of energy efficiency and underlying price elasticities. The analysis controls for plant level price endogeneity and heterogeneity to obtain a decomposition of efficiency into persistent (PE) and time-varying (TVE) components. Total inefficiency is relatively small and price elasticities are relatively high. If all plants performed at the 90th percentile of their efficiency distribution, the reduction in energy is between 4% and 13%. A modest carbon price of between $9.48/ton and $14.01/ton CO2 would achieve reductions in energy use equivalent to all manufacturing plants making improvements to close the efficiency gap.
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Business Dynamic Statistics of Innovative Firms
January 2017
Working Paper Number:
CES-17-72
A key driver of economic growth is the reallocation of resources from low to high productivity activities. Innovation plays an important role in this regard by introducing new products, services, and business methods that ultimately lead to increased productivity and rising living standards. Traditional measures of innovation, particularly those based on aggregate inputs, are increasingly unable to capture the breadth and depth of innovation in modern economies. In this paper, we describe an effort at the
US Census Bureau, the Business Dynamics Statistics of Innovative Firms (BDS-IF) project, which aims to address these challenges by extending the Business Dynamics Statistics data to include new measures of innovative activity. The BDS-IF project will produce measures of firm, establishment, and employment flows by firm age, firm size, and industry for the subset of firms engaged in activities related to innovation. These activities include patenting and trademarking, the employment of STEM workers, and R&D expenditures. The exibility of the underlying data infrastructure allows this measurement agenda to be extended to include copyright activity, management practices, and high growth firms.
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Making a Motivated Manager: A Census Data Investigation into Efficiency Differences Between Franchisee and Franchisor-Owned Restaurants
January 2016
Working Paper Number:
CES-16-54
While there has been significant research on the reasons for franchising, little work has examined the effects of franchising on establishment performance. This paper attempts to fill that gap. We use restricted-access US Census Bureau microdata from the 2007 Census of Retail Trade to examine establishment-level productivity of franchisee- and franchisor-owned restaurants. We do this by employing a two-stage data envelopment analysis model where the first stage uses DEA to measure each establishment's efficiency. The DEA efficiency score is then used as the second-stage dependent variable. The results show a strong and robust effect attributed to franchisee ownership for full service restaurants, but a smaller and insignificant difference for limited service restaurants. We believe the differences in task programability between limited and full service restaurants results in a very different role for managers/franchisees and is the driving factor behind the different results.
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Measuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis
January 2016
Working Paper Number:
CES-16-52
This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.
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Associations Between Public Housing and Individual Earnings in New Orleans
October 2015
Working Paper Number:
CES-15-32
This study uses a sample of the civilian labor force aged 16-64 constructed from the Decennial Census and American Community Survey, along with data from the HUD dataset Picture of Subsidized Households, to compare the likelihood for job earnings in relation to public housing developments in the New Orleans MSA before and after Hurricane Katrina. Results from a series of hierarchical linear models (HLM) indicate significant relationships are altered between time periods, including those from public and mixed-income developments, suggesting a fluid relationship between neighborhoods and economic outcomes during physical, demographic and economic restructuring.
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None
September 2014
Working Paper Number:
CES-14-35
This paper presents a novel empirical study of innovation practices of U.S. companies and their relation to productivity levels using new business micro data from the Business Research and Development and Innovation Survey (BRDIS) for the years 2008-2011. We use factor analysis to reduce a set of inputs and outputs of innovation activities into four latent unobserved innovation modes or practices. Companies are grouped according to their scores across the four factors to see that in large, small and medium companies more than one mode of innovation practices prevails. The next step in the analysis links different types of innovation practices to levels of productivity using regression analysis. The innovation modes have a statistically significant positive relation with the level of productivity. The paper demonstrates the possibility of taking into account the multidimensionality of innovation without the use of composite indicators.
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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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