-
Firms' Exporting Behavior under Quality Constraints
May 2009
Working Paper Number:
CES-09-13
We develop a model of international trade with export quality requirements and two dimensions of firm heterogeneity. In addition to "productivity", firms are also heterogeneous in their "caliber" {the ability to produce quality using fewer fixed inputs. Compared to singleattribute models of firm heterogeneity emphasizing either productivity or the ability to produce quality, our model provides a more nuanced characterization of firms' exporting behavior. In particular, it explains the empirical fact that firm size is not monotonically related with export status: there are small firms that export and large firms that only operate in the domestic market. The model also delivers novel testable predictions. Conditional on size, exporters are predicted to sell products of higher quality and at higher prices, pay higher wages and use capital more intensively. These predictions, although apparently intuitive, cannot be derived from singleattribute models of firm heterogeneity as they imply no variation in export status after size is controlled for. We find strong support for the predictions of our model in manufacturing establishment datasets for India, the U.S., Chile, and Colombia.
View Full
Paper PDF
-
Estimating the Distribution of Plant-Level Manufacturing Energy Efficiency with Stochastic Frontier Regression
March 2007
Working Paper Number:
CES-07-07
A feature commonly used to distinguish between parametric/statistical models and engineering models is that engineering models explicitly represent best practice technologies while the parametric/statistical models are typically based on average practice. Measures of energy intensity based on average practice are less useful in the corporate management of energy or for public policy goal setting. In the context of company or plant level energy management, it is more useful to have a measure of energy intensity capable of representing where a company or plant lies within a distribution of performance. In other words, is the performance close (or far) from the industry best practice? This paper presents a parametric/statistical approach that can be used to measure best practice, thereby providing a measure of the difference, or 'efficiency gap' at a plant, company or overall industry level. The approach requires plant level data and applies a stochastic frontier regression analysis to energy use. Stochastic frontier regression analysis separates the energy intensity into three components, systematic effects, inefficiency, and statistical (random) error. The stochastic frontier can be viewed as a sub-vector input distance function. One advantage of this approach is that physical product mix can be included in the distance function, avoiding the problem of aggregating output to define a single energy/output ratio to measure energy intensity. The paper outlines the methods and gives an example of the analysis conducted for a non-public micro-dataset of wet corn refining plants.
View Full
Paper PDF
-
The Importance of Reallocations in Cyclical Productivity and Returns to Scale: Evidence from Plant-Level Data
March 2007
Working Paper Number:
CES-07-05
This paper provides new evidence that estimates based on aggregate data will understate the true procyclicality of total factor productivity. I examine plant-level data and show that some industries experience countercyclical reallocations of output shares among firms at different points in the business cycle, so that during recessions, less productive firms produce less of the total output, but during expansions they produce more. These reallocations cause overall productivity to rise during recessions, and do not reflect the actual path of productivity of a representative firm over the course of the business cycle. Such an effect (sometimes called the cleansing effect of recessions) may also bias aggregate estimates of returns to scale and help explain why decreasing returns to scale are found at the industry-level data.
View Full
Paper PDF
-
Identifying Individual and Group Effects in the Presence of Sorting: A Neighborhood Effects Application
January 2007
Working Paper Number:
CES-07-03
Researchers have long recognized that the non-random sorting of individuals into groups generates correlation between individual and group attributes that is likely to bias naive estimates of both individual and group effects. This paper proposes a non-parametric strategy for identifying these effects in a model that allows for both individual and group unobservables, applying this strategy to the estimation of neighborhood effects on labor market outcomes. The first part of this strategy is guided by a robust feature of the equilibrium in the canonical vertical sorting model of Epple and Platt (1998), that there is a monotonic relationship between neighborhood housing prices and neighborhood quality. This implies that under certain conditions a non-parametric function of neighborhood housing prices serves as a suitable control function for the neighborhood unobservable in the labor market outcome regression. This control function converts the problem to a model with one unobservable so that traditional instrumental variables solutions may be applied. In our application, we instrument for each individual.s observed neighborhood attributes with the average neighborhood attributes of a set of observationally identical individuals. The neighborhood effects model is estimated using confidential microdata from the 1990 Decennial Census for the Boston MSA. The results imply that the direct effects of geographic proximity to jobs, neighborhood poverty rates, and average neighborhood education are substantially larger than the conditional correlations identified using OLS, although the net effect of neighborhood quality on labor market outcomes remains small. These findings are robust across a wide variety of specifications and robustness checks.
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 Dynamics of Plant-Level Productivity in U.S. Manufacturing
July 2006
Working Paper Number:
CES-06-20
Using a unique database that covers the entire U.S. manufacturing sector from 1976 until 1999, we estimate plant-level total factor productivity for a large number of plants. We characterize time series properties of plant-level idiosyncratic shocks to productivity, taking into account aggregate manufacturing-sector shocks and industry-level shocks. Plant-level heterogeneity and shocks are a key determinant of the cross-sectional variations in output. We compare the persistence and volatility of the idiosyncratic plant-level shocks to those of aggregate productivity shocks estimated from aggregate data. We find that the persistence of plant level shocks is surprisingly low-we estimate an average autocorrelation of the plantspecific productivity shock of only 0.37 to 0.41 on an annual basis. Finally, we find that estimates of the persistence of productivity shocks from aggregate data have a large upward bias. Estimates of the persistence of productivity shocks in the same data aggregated to the industry level produce autocorrelation estimates ranging from 0.80 to 0.91 on an annual basis. The results are robust to the inclusion of various measures of lumpiness in investment and job flows, different weighting methods, and different measures of the plants' capital stocks.
View Full
Paper PDF
-
Import Price Pressure on Firm Productivity and Employment: The Case of U.S. Textiles
March 2006
Working Paper Number:
CES-06-09
Theoretical research has predicted three different effects of increased import competition on plant-level behavior: reduced domestic production and sales, improving average efficiency of plants, and increased exit of marginal firms. In empirical work, though, such effects are difficult to separate from the impact of exogenous technological progress (or regress). I use detailed plant-level information available in the US Census of Manufacturers and the Annual Survey of Manufacturers for the period 1983-2000 to decompose these effects. I derive the relative contribution of technology and import competition to the increase in productivity and the decline in employment in textiles production in the US in recent years. I then simulate the impact of removal of quota protection on the scale of operation of the average plant and the incentive to plant closure. The methodology employs a number of important innovations in examining the impact of falling import prices on the domestic production of an import-competing good. First, import competition is modeled directly through its impact on the relative prices of monopolistically competitive goods along the lines suggested by Melitz (2000). Second, the effect of technology is incorporated through structural estimation of plant-level production functions in four factors (capital, labor, energy and materials). Solutions to econometric difficulties related to missing capital data and unobserved productivity are incorporated into the estimation technique. The model is estimated for plants with primary product in SIC 2211 (broadwoven cotton cloth). Results validate modeling demand as for differentiated products. Technological coefficients are sensible, with exogenous technological progress playing a large role. In the simulations run, the effects of foreign price competition are orders of magnitude higher than those of technological progress for the period after quotas on imports are removed. The large-scale reduction in employment and output in the US is shown to be a combination of reduced employment and output at plants in continuous operation and of plant closures that exceed new entries.
View Full
Paper PDF
-
A Flexible Test for Agglomeration Economies in Two U.S. Manufacturing Industries
August 2004
Working Paper Number:
CES-04-14
This paper uses the inverse input demand function framework of Kim (1992) to test for economies of industry and urban size in two U.S. manufacturing sectors of differing technology intensity: farm and garden machinery (SIC 352) and measuring and controlling devices (SIC 382). The inverse input demand framework permits the estimation of the production function jointly with a set of cost shares without the imposition of prior economic restrictions. Tests using plant-level data suggest the presence of population scale (urbanization) economies in the moderate- to low-technology farm and garden machinery sector and industry scale (localization) economies in the higher technology measuring and controlling devices sector. The efficiency and generality of the inverse input demand approach are particularly appropriate for micro-level studies of agglomeration economies where prior assumptions regarding homogeneity and homotheticity are less appropriate.
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
-
Estimating Measurement Error in SIPP Annual Job Earnings: A Comparison of Census Survey and SSA Administrative Data
September 2002
Working Paper Number:
tp-2002-24
The third chapter investigates measurement error in SIPP annual job
earnings data linked to SSA administrative earnings data. The multiple
earnings measures provided by the survey and administrative data enable
the identification of components of true variation and variation due to
measurement error. We find that 18% of the variation in SIPP annual job
earnings can be attributed to measurement error. We also find that in
both the SIPP and the DER, measurement error is persistent over time.
A lower level of auto-correlation in the SIPP measurement error than in
the economic error component leads to a lower reliability ratio of .62 for
first-differenced earnings.
View Full
Paper PDF
