Numerous empirical studies have examined the role of firm and industry heterogeneity in the decision to adopt new technologies using a Net Present Value framework. However, as suggested by the recently developed option-value theory, these studies may have overlooked the role of investment reversibility and uncertainty as important determinants of technology adoption. Using the option-value investment model as my underlying theoretical framework, I examine how these two factors affect the decision to adopt three advanced manufacturing technologies. My results support the option-value model's prediction that plants operating in industries facing higher investment reversibility and lower degrees of demand and technological uncertainty are more likely to adopt advanced manufacturing technologies.
-
Technology Usage in U.S. Manufacturing Industries: New Evidence from the Survey of Manufacturing Technology
October 1991
Working Paper Number:
CES-91-07
Using a new dataset on technology usage in U.S. manufacturing plants, this paper describes how technology usage varies by plant and firm characteristics. The paper extends the previous literature in three important ways. First, it examines a wide range of relatively new technologies. Second, the paper uses a much larger and more representative set of firms and establishments than previous studies. Finally, the paper explores the role of firm R&D expenditures in the process of technology adoption. The main findings indicate that larger plants more readily use new technologies, plants owned by firms with high R&D-to-sales ratios adopt technologies more rapidly, and the relationship between plant age and technology usage is relatively weak.
View Full
Paper PDF
-
Linking Investment Spikes and Productivity Growth: U.S. Food Manufacturing Industry
October 2008
Working Paper Number:
CES-08-36
We investigate the relationship between productivity growth and investment spikes using Census Bureau's plant-level data set for the U.S. food manufacturing industry. We find that productivity growth increases after investment spikes suggesting an efficiency gain or plants' learning effect. However, efficiency and the learning period associated with investment spikes differ among plants' productivity quartile ranks implying the differences in the plants' investment types such as expansionary, replacement or retooling. We find evidence of both convex and non-convex types of adjustment costs where lumpy plant-level investments suggest the possibility of non-convex adjustment costs and hazard estimation results suggest the possibility of convex adjustment costs. The downward sloping hazard can be due to the unobserved heterogeneity across plants such as plants' idiosyncratic obsolescence caused by different R&D capabilities and implies the existence of convex adjustment costs. Food plants frequently invest during their first few years of operation and high productivity plants postpone investing due to high fixed costs.
View Full
Paper PDF
-
The Role of Technological and Industrial Heterogeneity In Technology Diffusion: a Markovian Approach
February 2003
Working Paper Number:
CES-03-07
Recent empirical studies have established the importance of intra and inter-industry heterogeneity in investment in innovation and other outcomes. This paper examines the role of industry and technology heterogeneity in the diffusion of advanced manufacturing technologies from a simple Markovian approach. Using the Maximum Entropy estimator, I estimate transition probabilities and corresponding half-lives, look for outliers in technology and industry diffusion patterns, and try to find explanations of their unusual behavior in idiosyncratic technology and industry characteristics. A consistent industry-level pattern that emerged is one that relates consumer demand and production processes. It seems that in industries where hand-made products are a sign of quality to the customer, technology spreads very slowly. On the other hand, in industries where demand for sophisticated, high-precision goods is high or in industries where demand-driven product specifications vary quite rapidly over relatively short periods of time, advanced technologies diffuse much more rapidly.
View Full
Paper PDF
-
The Survival of Industrial Plants
October 2002
Working Paper Number:
CES-02-25
The study seeks to explain the attrition rate of new manufacturing plants in the United States in terms of three vectors of variables. The first explains how survival of the fittest proceeds through learning by firms (plants) about their own relative efficiency. The second explains how efficiency systematically changes over time and what augments or diminishes it. The third captures the opportunity cost of resources employed in a plant. The model is tested using maximum-likelihood probit analysis with very large samples for successive census years in the 1967-97 period. One sample consists of an unbalanced panel of about three-fourths of a million plants of single and multi-unit firms, or alternatively of about 300,000 plants if only the most reliable data are considered. The second is restricted to the plants of multi-unit firms in the same time span and consists of an unbalanced panel of more than 100,000 plants. The empirical analysis strongly confirms the predictions of the model.
View Full
Paper PDF
-
Why Are Plant Deaths Countercyclical: Reallocation Timing or Fragility?
November 2006
Working Paper Number:
CES-06-24
Because plant deaths destroy specific capital with large local economic impacts and potentially important macroeconmic effects, understanding the causes of deaths and, in particular, why they are concentrated in cyclical downturns, is important. The reallocationtiming hypothesis posits that plants suffering adverse permanent demand/productivity shocks delay shutdowns until cyclical downturns when plant capacity is less valuable, while the fragility hypothesis posits that shutdowns occur in downturns because the option value of maintaining the plant through low profitability periods is too small. I show that the effect that a plant's specific capital has on the timing of plant deaths differs across these two hypotheses and then use this insight to test the hypotheses' relative importance. I find that fragility is the dominant cause of the countercyclical behavior of plant deaths. This suggests that the endogenous destruction of capital is likely an important amplification and propagation mechanism for cyclical shocks and that stabilization policies have the benefit of reduced capital destruction.
View Full
Paper PDF
-
The Missing Link: Technology, Productivity, and Investment
October 1995
Working Paper Number:
CES-95-12
This paper examines the relationship between productivity, investment, and age for over 14,000 plants in the U.S. manufacturing sector in the 1972-1988 period. Productivity patterns vary significantly due to plant heterogeneity. Productivity first increases and then decreases with respect to plant age, and size and industry are systematically correlated with productivity and productivity growth. However, there is virtually no observable relationship between investment and productivity or productivity growth. Overall, the results indicate that plant heterogeneity and fixed effects are more important determinants of observable productivity patterns than sunk costs or capital reallocation. Key Words: productivity, investment, technical change
View Full
Paper PDF
-
The Demand for Human Capital: A Microeconomic Approach
December 2001
Working Paper Number:
CES-01-16
We propose a model for explaining the demand for human capital based on a CES production function with human capital as an explicit argument in the function. The resulting factor demand model is tested with data on roughly 6,000 plants from the Census Bureau's Longitudinal Research Database. The results show strong complementarity between physical and human capital. Moreover, the complementarity is greater in high than in low technology industries. The results also show that physical capital of more recent vintage is associated with a higher demand for human capital. While the age of a plant as a reflection of learning-by-doing is positively related to the accumulation of human capital, this relation is more pronounced in low technology industries.
View Full
Paper PDF
-
The Life Cycles of Industrial Plants
October 2001
Working Paper Number:
CES-01-10
The paper presents a dynamic programming model with multiple classes of capital goods to explain capital expenditures on existing plants over their lives. The empirical specification shows that the path of capital expenditures is explained by (a) complementarities between old and new capital goods, (b) the age of plants, (c) an index that captures the rate of technical change and (d) the labor intensiveness of a plant when it is newly born. The model is tested with Census data for roughly 6,000 manufacturing plants that were born after 1972.
View Full
Paper PDF
-
Technology Locks, Creative Destruction And Non-Convergence In Productivity Levels
April 1995
Working Paper Number:
CES-95-06
This paper presents a simple solution to a new model that seeks to explain the distribution of plants across productivity levels within an industry, and empirically confirms some key predictions using the U.S. textile industry. In the model, plants are locked into a given productivity level, until they exit or retool. Convex costs of adjustment captures the fact that more productive plants expand faster. Provided there is technical change, productivity levels do not converge; the model achieves persistent dispersion in productivity levels within the context of a distortion free competitive equilibrium. The equilibrium, however, is rather turbulent; plants continually come on line with the cutting edge technology, gradually expand and finally exit or retool when they cease to recover their variable costs. The more productive plants create jobs, while the less productive destroy them. The model establishes a close link between productivity growth and dispersion in productivity levels; more rapid productivity growth leads to more widespread dispersion. This prediction is empirically confirmed. Additionally, the model provides an explanation for S-shaped diffusion.
View Full
Paper PDF
-
Employment Adjustment Costs and Establishment Characteristics
November 1999
Working Paper Number:
CES-99-15
Microeconomic employment adjustment costs affect not only employment adjustments at the micro level but may also profoundly impact aggregate employment dynamics. This paper sheds light on the nature of these microeconomic employment adjustment costs and quantifies their impact on aggregate employment dynamics. The empirical exercises in the paper analyze the differences in employment adjustments by establishment characteristics within a hazard model framework using micro data for approximately 10,000 U.S. manufacturing plants. I find that employment adjustments vary systematically by establishment characteristics; moreover, these variations suggest that employment adjustment costs reflect the technology of the plant, the skill of its workforce, and the plant's access to capital markets. Concerning the structure of the adjustment costs, the employment adjustments have significant nonlinearities and asymmetries consistent with nonconvex, asymmetric adjustment costs. Specifically, employment adjustment behavior shows substantial inertia in the face of large employment surpluses, varied adjustment behavior for small deviations from desired employment, and (S,s)-type of bimodal adjustments in response to large employment shortages. Finally, the micro level heterogeneity, asymmetries, and nonlinearities significantly impact sectoral and aggregate employment dynamics.
View Full
Paper PDF