Creative Destruction or Just Plain Destruction?: The U.S. Textile and Apparel Industries since 1972

Levinsohn, Jim; Petropoulos, Wendy

doi:10.3386/w8348

Cited by 27 publications

(24 citation statements)

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“…However, a recent study on the U.S. textile industry finds a similar importance of within plant changes, see Levinsohn and Petropoulos (2001).…”

Section: What Drives Aggregate Productivity Growth?mentioning

confidence: 99%

Revisiting Some Productivity Debates

Biesebroeck

2003

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Researchers interested in estimating productivity can choose from an array of methodologies, each with its strengths and weaknesses. Methods differ by the assumptions they rely on and imply very different calculations. I compare five widely used techniques: (a) index numbers, (b) data envelopment analysis, and three parametric methods, (c) instrumental variables estimation, (d) stochastic frontiers, and (e) semi-parametric estimation. I compare the estimates directly and evaluate three productivity debates using a panel of manufacturing plants in Colombia. The different methods generate surprisingly similar results. Correlations between alternative productivity estimates are invariably high. All methods confirm that exporters are more productive on average and that only a small portion of the productivity advantage is due to scale economies. Productivity growth is correlated more strongly with export status, frequent investments in capital equipment, and employment of managers than with the use of imported inputs or foreign ownership. On the debate whether aggregate productivity growth is driven by plant-level changes or output share relocation, all methods point to the importance of plant-level changes, in contrast to results from the U.S. MotivationProductivity is used and discussed widely. Ever since Solow (1957) decomposed output growth into the contribution of input growth and a residual productivity term, the concept has increased in popularity. Productivity has generated a lot of interest in its own right and is used as a benchmark to rank firms or countries. Such rankings gained credibility once other studies documented that productivity is correlated with other indicators of success such as employment growth, export status, or technology adoption. Low productivity has also been found to predict exit, the ultimate performance standard. Its importance can also be gauged from the attention it receives as a criterion to evaluate policy interventions or firms' decisions.In industrial economics, for example, a large literature investigates the effect of R&D on productivity and the resulting impact on industry structure. In international economics, efforts to evaluate the impact of trade liberalization has turned from estimating changes in price-cost margins to productivity changes.Fundamentally, the objective of productivity measurement is to identify output differences that cannot be explained by input differences. Because the production technology of each firm and the input tradeoff it allows, is not observed, our ability to control for input substitution is subject to error. In addition, inputs and outputs are likely to be measured with error, certainly in less intensively used data sets from developing countries. Methodologies for productivity measurement differ vastly in their sensitivity to measurement and specification error. 1I evaluate five widely-used methodologies, which fall in three broad classes. The first two, index numbers and data envelopment analysis, are flexible in the specific...

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“…However, a recent study on the U.S. textile industry finds a similar importance of within plant changes, see Levinsohn and Petropoulos (2001).…”

Section: What Drives Aggregate Productivity Growth?mentioning

confidence: 99%

Revisiting Some Productivity Debates

Biesebroeck

2003

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“…productivity improvements within plants are, in general, the most important component of aggregate productivity growth, and~b! new entrants to the industry tend to be more productive than the firms that exit~Bartelsman & Doms, 2000;Foster, Haltiwanger, & Krizan, 1998, 2001!+ Although within plant productivity improvement tends to be the most dominant contributor to aggregate productivity growth, these empirical studies still show that the net entry of more productive plants contributes positively to growth+ Note, however, that all of the empirical studies cited above have not specifically examined the role of productivity dynamics in the food manufacturing industry~or the meatprocessing subsector! of a low-middle-income economy like Turkey+ There are a number of studies that decomposed productivity growth in agriculture~Ahmad & Bravo- Ureta, 1995;Brummer, Glauben, & Thijssen, 2002;Mamatzakis, 2003!…”

Section: Introductionmentioning

confidence: 99%

Plant-level dynamics and aggregate productivity growth in the Turkish meat-processing industry: Evidence from longitudinal data

Yaşar

Rejesus

Mintemur³

2006

Agribusiness

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The authors examine how plant-level dynamics contribute to aggregate productivity growth in the Turkish meat-processing industry. An aggregate productivity decomposition approach that utilizes plant-level longitudinal data is used to achieve this goal. Their results are consistent with the empirical literature in the sense that productivity enhancement within existing plants is the main source of aggregate productivity growth in this sector. However, their analysis generally suggests that plants that exit the meat-processing industry tend to be more productive than entering plants, especially in the posteconomic crisis period studied. Even though the latter insight is not consistent with the existing empirical literature, they show that these results tend to support R. Caballero and M. Hammour's (2000) contention that institutional factors such as industry structure (i.e., mature vs. infant industry) and economic crisis conditions (i.e., pre- vs. postcrisis periods) affect the nature of plant dynamics' contributions to aggregate productivity growth. Overall, the study's results reveal that industry-specific institutional factors must be taken into consideration when shaping policies aimed to improve and sustain aggregate productivity growth. [JEL Classifications: D24, L25, O12]. © 2006 Wiley Periodicals, Inc. Agribusiness 22: 91-107, 2006.

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“…However, a very different picture emerges from data from the individual sectors of the textile industry where there is tremendous creative energy. Levinsohn and Petropolous (2001) present the industry as an example of "creative destruction", a term made famous by Joseph Schumpeter. His idea is that the creation of new products and production methods lead to the destruction of market share for firms committed to existing paradigms.…”

Section: Introductionmentioning

confidence: 99%