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Cheaper by the Dozen: Using Sibling Discounts at Catholic Schools to Estimate the Price Elasticity of Private School Attendance
October 2011
Working Paper Number:
CES-11-34
The effect of vouchers on sorting between private and public schools depends upon the price elasticity of demand for private schooling. Estimating this elasticity is empirically challenging because prices and quantities are jointly determined in the market for private schooling. We exploit a unique and previously undocumented source of variation in private school tuition to estimate this key parameter. A majority of Catholic elementary schools offer discounts to families that enroll more than one child in the school in a given year. Catholic school tuition costs therefore depend upon the interaction of the number and spacing of a family's children with the pricing policies of the local school. This within-neighborhood variation in tuition prices allows us to control for unobserved determinants of demand with a fine set of geographic fixed effects, while still identifying the price parameter. We use data from 3700 Catholic schools, matched to restricted Census data that identifies geography at the block level. We find that a standard deviation decrease in tuition prices increases the probability that a family will send its children to private school by one-half percentage point, which translates into an elasticity of Catholic school attendance with respect to tuition costs of -0.19. Our subgroup results suggest that a voucher program would disproportionately induce into private schools those who, along observable dimensions, are unlike those who currently attend private school.
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Using the Survey of Plant Capacity to Measure Capital Utilization
July 2011
Working Paper Number:
CES-11-19
Most capital in the United States is idle much of the time. By some measures, the average workweek of capital in U.S. manufacturing is as low as 55 hours per 168 hour week. The level and variability of capital utilization has important implications for understanding both the level of production and its cyclical fluctuations. This paper investigates a number of issues relating to aggregation of capital utilization measures from the Survey of Plant Capacity and makes recommendations on expanding and improving the published statistics deriving from the Survey of Plant Capacity. The paper documents a number of facts about properties of capital utilization. First, after growing for decades, capital utilization started to fall in mid 1990s. Second, capital utilization is a useful predictor of changes in capacity utilization and other factors of production. Third, adjustment of productivity measures for variable capital utilization improves statistical and economic properties of these measures. Fourth, the paper constructs weights to aggregate firm level capital utilization rates to industry and economy level, which is the major enhancement to available data.
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Plant-Level Productivity and Imputation of Missing Data in the Census of Manufactures
January 2011
Working Paper Number:
CES-11-02
In the U.S. Census of Manufactures, the Census Bureau imputes missing values using a combination of mean imputation, ratio imputation, and conditional mean imputation. It is wellknown that imputations based on these methods can result in underestimation of variability and potential bias in multivariate inferences. We show that this appears to be the case for the existing imputations in the Census of Manufactures. We then present an alternative strategy for handling the missing data based on multiple imputation. Specifically, we impute missing values via sequences of classification and regression trees, which offer a computationally straightforward and flexible approach for semi-automatic, large-scale multiple imputation. We also present an approach to evaluating these imputations based on posterior predictive checks. We use the multiple imputations, and the imputations currently employed by the Census Bureau, to estimate production function parameters and productivity dispersions. The results suggest that the two approaches provide quite different answers about productivity.
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Computer Networks and Productivity Revisited: Does Plant Size Matter? Evidence and Implications
September 2010
Working Paper Number:
CES-10-25
Numerous studies have documented a positive association between information technology (IT) investments and business- and establishment-level productivity, but these studies usually pay sole or disporportionate attention to small- or medium-sized entities. In this paper, we revisit the evidence for manufacturing plants presented in Atrostic and Nguyen (2005) and show that the positive relationship between computer networks and labor productivity is only found among small- and medium-sized plants. Indeed, for larger plants the relationship is negative, and employment-weighted estimates indicate computer networks have a negative relationship with the productivity of employees, on average. These findings indicate that computer network investments may have an ambiguous relationship with aggregate labor productivity growth.
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Who Creates Jobs? Small vs. Large vs. Young
August 2010
Working Paper Number:
CES-10-17
There's been a long, sometimes heated, debate on the role of firm size in employment growth. Despite skepticism in the academic community, the notion that growth is negatively related to firm size remains appealing to policymakers and small business advocates. The widespread and repeated claim from this community is that most new jobs are created by small businesses. Using data from the Census Bureau Business Dynamics Statistics and Longitudinal Business Database, we explore the many issues regarding the role of firm size and growth that have been at the core of this ongoing debate (such as the role of regression to the mean). We find that the relationship between firm size and employment growth is sensitive to these issues. However, our main finding is that once we control for firm age there is no systematic relationship between firm size and growth. Our findings highlight the important role of business startups and young businesses in U.S. job creation. Business startups contribute substantially to both gross and net job creation. In addition, we find an 'up or out' dynamic of young firms. These findings imply that it is critical to control for and understand the role of firm age in explaining U.S. job creation.
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National Estimates of Gross Employment and Job Flows from the Quarterly Workforce Indicators with Demographic and Industry Detail
June 2010
Working Paper Number:
CES-10-11
The Quarterly Workforce Indicators (QWI) are local labor market data produced and released every quarter by the United States Census Bureau. Unlike any other local labor market series produced in the U.S. or the rest of the world, the QWI measure employment flows for workers (accession and separations), jobs (creations and destructions) and earnings for demographic subgroups (age and gender), economic industry (NAICS industry groups), detailed geography (block (experimental), county, Core- Based Statistical Area, and Workforce Investment Area), and ownership (private, all) with fully interacted publication tables. The current QWI data cover 47 states, about 98% of the private workforce in those states, and about 92% of all private employment in the entire economy. State participation is sufficiently extensive to permit us to present the first national estimates constructed from these data. We focus on worker, job, and excess (churning) reallocation rates, rather than on levels of the basic variables. This permits comparison to existing series from the Job Openings and Labor Turnover Survey and the Business Employment Dynamics Series from the Bureau of Labor Statistics. The national estimates from the QWI are an important enhancement to existing series because they include demographic and industry detail for both worker and job flow data compiled from underlying micro-data that have been integrated at the job and establishment levels by the Longitudinal Employer-Household Dynamics Program at the Census Bureau. The estimates presented herein were compiled exclusively from public-use data series and are available for download.
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An Alternative Theory of the Plant Size Distribution with an Application to Trade
May 2010
Working Paper Number:
CES-10-10
There is wide variation in the sizes of manufacturing plants, even within the most narrowly defined industry classifications used by statistical agencies. Standard theories attribute all such size differences to productivity differences. This paper develops an alternative theory in which industries are made up of large plants producing standardized goods and small plants making custom or specialty goods. It uses confidential Census data to estimate the parameters of the model, including estimates of plant counts in the standardized and specialty segments by industry. The estimated model fits the data relatively well compared with estimates based on standard approaches. In particular, the predictions of the model for the impacts of a surge in imports from China are consistent with what happened to U.S. manufacturing industries that experienced such a surge over the period 1997'2007. Large-scale standardized plants were decimated, while small-scale specialty plants were relatively less impacted.
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Building New Plants or Entering by Acquisition? Estimation of an Entry Model for the U.S. Cement Industry
April 2010
Working Paper Number:
CES-10-08
In many industries, firms usually have two choices when expanding into new markets: They can either build a new plant (greenfield entry) or they can acquire an existing incumbent. The U.S. cement industry is a clear example. For this industry, I study the effect of two policies on the entry behavior and industry equilibrium: An asymmetric environmental policy that creates barriers to greenfield entry and a policy that creates barriers to entry by acquisition (like an antitrust policy). In the U.S. cement industry, the comparative advantage (e.g., TFP or size) of entrants versus incumbents and the regulatory entry barriers are important factors that determine the means of expansion. To model this industry, I use a perfect information static entry game. To estimate the supply and demand primitives of my model, I apply a recent estimator of discrete games to a rich database of the U.S. Census of Manufactures for the years 1963-2002. In my counterfactual analyses, I find that a less favorable environment for mergers during the Reagan-Bush administration would decrease the acquired plants by 70% and increase the new plants by 20%. Also, I find that the Clean Air Act Amendments of 1990 increased the number of acquisitions by 7.8%. Furthermore, my simulations suggest that regulations that create barriers to greenfield entry are less favorable in terms of welfare than regulations that create barriers to entry by acquisition. Finally, I demonstrate how my parameter estimates change when I apply the traditional approach in the entry literature where entry by acquisition is not considered, and when using a simple OLS estimation.
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Euler-Equation Estimation for Discrete Choice Models: A Capital Accumulation Application
January 2010
Working Paper Number:
CES-10-02
This paper studies capital adjustment at the establishment level. Our goal is to characterize capital adjustment costs, which are important for understanding both the dynamics of aggregate investment and the impact of various policies on capital accumulation. Our estimation strategy searches for parameters that minimize ex post errors in an Euler equation. This strategy is quite common in models for which adjustment occurs in each period. Here, we extend that logic to the estimation of parameters of dynamic optimization problems in which non-convexities lead to extended periods of investment inactivity. In doing so, we create a method to take into account censored observations stemming from intermittent investment. This methodology allows us to take the structural model directly to the data, avoiding time-consuming simulation based methods. To study the effectiveness of this methodology, we first undertake several Monte Carlo exercises using data generated by the structural model. We then estimate capital adjustment costs for U.S. manufacturing establishments in two sectors.
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On Spatial Heterogeneity in Environmental Compliance Costs
September 2009
Working Paper Number:
CES-09-25R
This paper examines the extent of variation in regulatory stringency below the state level, using establishment-level data from the U.S. Census Bureau's Pollution Abatement Costs and Expenditures (PACE) survey to estimate a county-level index of environmental compliance costs (ECC). County-level variation is found to explain 11-18 times more of the variation in ECC than state-level variation alone, and the range of ECC within a state is often large. At least 34% of U.S. counties have ECC that are statistically different from their states'. Results suggest that important spatial variation is lost in state-level studies of environmental regulation.
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