Papers Containing Keywords(s): 'estimator'
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John M. Abowd - 3
Viewing papers 21 through 30 of 32
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Working PaperLong Term Effects of Military Service on the Distribution of Earnings
August 2009
Working Paper Number:
CES-09-17
I estimate the long term effect of military service on quantiles of earnings and education using the Vietnam draft lottery eligibility status as an instrument. I compare the local quantile treatment effect estimator studied by Abadie, Angrist, and Imbens (2002) to the instrumental variables quantile regression technique developed by Chernozhukov and Hansen (2008). Ordinary quantile regression shows a large negative association between service in Vietnam and earnings of white men, with the effect increasing in magnitude for the upper quantiles. Quantile treatment effects estimates show the opposite pattern, although much smaller in magnitude, with a small negative effect at the lower end of the distribution, and a small positive effect at the upper end. This suggests the ordinary quantile result is due to heterogeneous selection effects. The two methods of quantile treatment effects estimation give similar results.View Full Paper PDF
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Working PaperMeasuring Inequality Using Censored Data: A Multiple Imputation Approach
April 2009
Working Paper Number:
CES-09-05
To measure income inequality with right censored (topcoded) data, we propose multiple imputation for censored observations using draws from Generalized Beta of the Second Kind distributions to provide partially synthetic datasets analyzed using complete data methods. Estimation and inference uses Reiter's (Survey Methodology 2003) formulae. Using Current Population Survey (CPS) internal data, we find few statistically significant differences in income inequality for pairs of years between 1995 and 2004. We also show that using CPS public use data with cell mean imputations may lead to incorrect inferences about inequality differences. Multiply-imputed public use data provide an intermediate solution.View Full Paper PDF
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Working PaperThe 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
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Working PaperPollution Abatement Expenditures and Plant-Level Productivity: A Production Function Approach
August 2003
Working Paper Number:
CES-03-16
In this paper, we investigate the impact of environmental regulation on productivity using a Cobb-Douglas production function framework. Estimating the effects of regulation on productivity can be done with a top-down approach using data for broad sectors of the economy, or a more disaggregated bottom-up approach. Our study follows a bottom-up approach using data from the U.S. paper, steel, and oil industries. We measure environmental regulation using plant-level information on pollution abatement expenditures, which allows us to distinguish between productive and abatement expenditures on each input. We use annual Census Bureau information (1979-1990) on output, labor, capital, and material inputs, and pollution abatement operating costs and capital expenditures for 68 pulp and paper mills, 55 oil refineries, and 27 steel mills. We find that pollution abatement inputs generally contribute little or nothing to output, especially when compared to their '''productive''' equivalents. Adding an aggregate pollution abatement cost measure to a Cobb-Douglas production function, we find that a $1 increase in pollution abatement costs leads to an estimated productivity decline of $3.11, $1.80, and $5.98 in the paper, oil, and steel industries respectively. These findings imply substantial differences across industries in their sensitivity to pollution abatement costs, arguing for a bottom-up approach that can capture these differences. Further differentiating plants by their production technology, we find substantial differences in the impact of pollution abatement costs even within industries, with higher marginal costs at plants with more polluting technologies. Finally, in all three industries, plants concentrating on change-in-production-process abatement techniques have higher productivity than plants doing predominantly end-of-line abatement, but also seem to be more affected by pollution abatement operating costs. Overall, our results point to the importance using detailed, disaggregated analyses, even below the industry level, when trying to model the costs of forcing plants to reduce their emissions.View Full Paper PDF
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Working PaperEstimating 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
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Working PaperWhy Some Firms Export
June 2001
Working Paper Number:
CES-01-05
This paper presents a dynamic model of the export decision by a profit-maximizing firm. Using a panelofU.S.manufacturing plants, we test for the role of plant characteristics, spillovers from neighboring exporters, entry costs and government export promotion expenditures. Entry and exit in the export market by U.S. plants is substantial, past exporters are apt to reenter, and plants are likely to export in consecutive years. However, we find that entry costs are significant and spillovers from the export activity of other plants negligible. State export promotion expenditures have no significant effect on the probability of exporting. Plant characteristics, especially those indicative of past success, strongly increase the probability of exporting as do favorable exchange rate shocks.View Full Paper PDF
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Working PaperAn Economist's Primer on Survey Samples
September 2000
Working Paper Number:
CES-00-15
Survey data underlie most empirical work in economics, yet economists typically have little familiarity with survey sample design and its effects on inference. This paper describes how sample designs depart from the simple random sampling model implicit in most econometrics textbooks, points out where the effects of this departure are likely to be greatest, and describes the relationship between design-based estimators developed by survey statisticians and related econometric methods for regression. Its intent is to provide empirical economists with enough background in survey methods to make informed use of design-based estimators. It emphasizes surveys of households (the source of most public-use files), but also considers how surveys of businesses differ. Examples from the National Longitudinal Survey of Youth of 1979 and the Current Population Survey illustrate practical aspects of design-based estimation.View Full Paper PDF
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Working PaperIndustrial Spillovers In Developing Countries: Plant-Level Evidence From Chile, Mexico And Morocco
January 1998
Working Paper Number:
CES-98-02
Recent trade and growth models have underscored the potential importance of external economies of scale. However, many of the most frequently modeled externalities have either not been measured or have been estimated with data too aggregate to be informative. In this paper, plant-level longitudinal data from Chile, Mexico and Morocco allow me to provide some of the first micro evidence on several types of external economies from plant-level production functions. The results indicate that in many industries own-industry output contributes positively to plant-level productivity. However, the effects of geographic concentration are mixed. Cross-country concentration, as measured by a geographic GINI index, often decreases productivity but within-province, same industry activity enhances it.View Full Paper PDF
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Working PaperThe Long-Run Demand for Labor: Estimates From Census Establishment Data
September 1993
Working Paper Number:
CES-93-13
This paper estimates long-run demand functions for production workers, production worker hours, and nonproduction workers using micro data from U.S. establishment surveys. The paper focuses on estimation of the wage and output elasticities of labor demand using data on over 41,000 U.S. manufacturing plants in 1975 and more than 30,000 plants in 1981. Particular attention is focused on the problems of unobserved producer heterogeneity and measurement errors in output that can affect labor demand estimates based on establishment survey data. The empirical results reveal that OLS estimates of both the own-price elasticity and the output elasticity of labor demand are biased downward as a result of unobserved heterogeneity. Differencing the data as a solution to this problem greatly exaggerates measurement error in the output coefficients. The use of capital stocks as instrumental variables to correct for measurement error in output significantly alters output elasticities in the expected direction but has no systematic effect on own-price elasticities. All of these patterns are found in estimates that pool establishment data across industries and in industry-specific regressions for the vast majority of industries. Estimates of the output elasticity of labor demand indicate that there are slight increasing returns for production workers and production hours, with a pooled data estimate of .92. The estimate for nonproduction workers in .98. The variation in the output elasticities across industries is fairly small. Estimates of the own-price elasticity vary more substantially with the year, type of differencing used, and industry. They average -.50 for production hours, -.41 for production workers, and -.44 for nonproduction workers. The price elasticities vary widely across manufacturing industries: the interquartile range for the industry estimates is approximately .40.View Full Paper PDF
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Working PaperThe Dynamics Of Productivity In The Telecommunications Equipment Industry
February 1992
Working Paper Number:
CES-92-02
Technological change and deregulation have caused a major restructuring of the telecommunications equipment industry over the last two decades. We estimate the parameters of a production function for the equipment industry and then use those estimates to analyze the evolution of plant-level productivity over this period. The restructuring involved significant entry and exit and large changes in the sizes of incumbents. Since firms choices on whether to liquidate and the on the quantities of inputs demanded should they continue depend on their productivity, we develop an estimation algorithm that takes into account the relationship between productivity on the one hand, and both input demand and survival on the other. The algorithm is guided by a dynamic equilibrium model that generates the exit and input demand equations needed to correct for the simultaneity and selection problems. A fully parametric estimation algorithm based on these decision rules would be both computationally burdensome and require a host of auxiliary assumptions. So we develop a semiparametric technique which is both consistent with a quite general version of the theoretical framework and easy to use. The algorithm produces markedly different estimates of both production function parameters and of productivity movements than traditional estimation procedures. We find an increase in the rate of industry productivity growth after deregulation. This in spite of the fact that there was no increase in the average of the plants' rates of productivity growth, and there was actually a fall in our index of the efficiency of the allocation of variable factors conditional on the existing distribution of fixed factors. Deregulation was, however, followed by a reallocation of capital towards more productive establishments (by a down sizing, often shutdown, of unproductive plants and by a disproportionate growth of productive establishments) which more than offset the other factors' negative impacts on aggregate productivity.View Full Paper PDF
