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Papers Containing Keywords(s): 'expenditure'

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Center for Economic Studies - 72

Annual Survey of Manufactures - 70

Census of Manufactures - 51

Bureau of Economic Analysis - 51

Total Factor Productivity - 48

North American Industry Classification System - 48

Ordinary Least Squares - 46

Bureau of Labor Statistics - 44

National Science Foundation - 44

Longitudinal Research Database - 41

Longitudinal Business Database - 40

Standard Industrial Classification - 38

National Bureau of Economic Research - 37

Cobb-Douglas - 31

Environmental Protection Agency - 29

Internal Revenue Service - 26

Current Population Survey - 25

Census Bureau Disclosure Review Board - 24

Economic Census - 24

Census of Manufacturing Firms - 22

Chicago Census Research Data Center - 20

Federal Statistical Research Data Center - 19

Pollution Abatement Costs and Expenditures - 19

Federal Reserve Bank - 18

American Community Survey - 18

Medical Expenditure Panel Survey - 18

Standard Statistical Establishment List - 17

Business Register - 15

Census Bureau Longitudinal Business Database - 15

Agency for Healthcare Research and Quality - 15

Disclosure Review Board - 14

Special Sworn Status - 14

Survey of Industrial Research and Development - 13

Manufacturing Energy Consumption Survey - 13

Research Data Center - 12

PAOC - 12

Census Bureau Business Register - 11

National Income and Product Accounts - 11

Federal Reserve System - 11

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Decennial Census - 11

Energy Information Administration - 11

National Ambient Air Quality Standards - 11

National Center for Health Statistics - 10

Generalized Method of Moments - 10

Social Security - 10

Journal of Economic Literature - 10

Department of Labor - 9

Longitudinal Employer Household Dynamics - 9

University of Chicago - 9

General Accounting Office - 9

Service Annual Survey - 9

Employer Identification Numbers - 8

Business Research and Development and Innovation Survey - 8

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Bureau of Labor - 8

Michigan Institute for Teaching and Research in Economics - 8

Survey of Manufacturing Technology - 8

Alfred P Sloan Foundation - 7

Social Security Administration - 7

Protected Identification Key - 7

TFPQ - 7

New York University - 7

Department of Economics - 7

Council of Economic Advisers - 7

Census Bureau Center for Economic Studies - 7

National Academy of Sciences - 6

2010 Census - 6

Information and Communication Technology Survey - 6

Organization for Economic Cooperation and Development - 6

Office of Management and Budget - 6

Fabricated Metal Products - 6

American Economic Review - 6

Boston Research Data Center - 6

Auxiliary Establishment Survey - 6

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Federal Government - 5

Consumer Expenditure Survey - 5

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New York Times - 5

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W-2 - 5

UC Berkeley - 5

Duke University - 5

State Energy Data System - 5

Establishment Micro Properties - 5

University of Maryland - 5

COMPUSTAT - 5

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Urban Institute - 5

Review of Economics and Statistics - 5

Department of Agriculture - 5

Supreme Court - 5

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National Research Council - 5

Department of Commerce - 5

Financial, Insurance and Real Estate Industries - 5

Occupational Employment Statistics - 4

Quarterly Census of Employment and Wages - 4

Business R&D and Innovation Survey - 4

Securities and Exchange Commission - 4

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Survey of Income and Program Participation - 4

Business Services - 4

Small Business Administration - 4

Department of Homeland Security - 4

European Commission - 4

Kauffman Foundation - 4

Characteristics of Business Owners - 4

Social and Economic Supplement - 4

Cornell University - 4

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E32 - 4

Federal Trade Commission - 4

Cornell Institute for Social and Economic Research - 4

Toxics Release Inventory - 4

Labor Productivity - 4

Computer Network Use Supplement - 4

Electronic Data Interchange - 4

Department of Defense - 3

Retail Trade - 3

Technical Services - 3

University of Texas - 3

Board of Governors - 3

Longitudinal Firm Trade Transactions Database - 3

Net Present Value - 3

Temporary Assistance for Needy Families - 3

Washington University - 3

NBER Summer Institute - 3

Business Dynamics Statistics - 3

Person Validation System - 3

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CPS ASEC - 3

International Trade Commission - 3

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Boston College - 3

Code of Federal Regulations - 3

National Institutes of Health - 3

Research and Development - 3

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Journal of Labor Economics - 3

University of Michigan - 3

Department of Justice - 3

Medicaid Services - 3

Ohio State University - 3

Center for Research in Security Prices - 3

Department of Energy - 3

Business Master File - 3

Journal of Political Economy - 3

Yale University - 3

Harvard University - 3

New England County Metropolitan - 3

Statistics Canada - 3

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American Statistical Association - 3

Columbia University - 3

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technology - 16

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pollution abatement - 16

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healthcare - 16

productivity measures - 15

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spillover - 14

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respondent - 12

population - 12

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medicaid - 10

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firms productivity - 6

census data - 6

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imputation - 5

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productivity variation - 5

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patent - 5

rent - 5

employment growth - 5

schooling - 5

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utility - 5

study - 5

research - 5

pollution regulation - 5

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taxation - 5

state - 5

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enrollee - 5

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analysis - 5

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occupation - 4

labor statistics - 4

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export - 4

productivity shocks - 4

sector productivity - 4

family - 4

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productivity size - 4

practices productivity - 4

metropolitan - 4

city - 4

funding - 4

education - 4

microdata - 4

research census - 4

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financing - 4

patenting - 4

exogeneity - 4

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taxable - 4

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regional economic - 4

utilization - 4

health - 4

economic statistics - 4

dependent - 4

pension - 4

benefit - 4

insurer - 4

regressing - 4

coverage employer - 4

use census - 4

resident - 4

merger - 4

wholesale - 4

equilibrium - 4

management - 4

retiree - 4

manufacturing plants - 4

compliance - 4

productivity differences - 4

industry concentration - 4

specialization - 4

census years - 4

computer - 4

observed productivity - 4

imputation model - 3

information census - 3

commerce - 3

percentile - 3

good - 3

purchase - 3

prospect - 3

disparity - 3

maternal - 3

sectoral - 3

residential - 3

exogenous - 3

entry productivity - 3

larger firms - 3

firms size - 3

school - 3

level productivity - 3

outsourcing - 3

innovative - 3

earns - 3

externality - 3

industry heterogeneity - 3

region - 3

technical - 3

statistician - 3

imputed - 3

surveys censuses - 3

subsidized - 3

incorporated - 3

fund - 3

investor - 3

firm innovation - 3

census business - 3

geographically - 3

policymakers - 3

estimates employment - 3

insurance employer - 3

manager - 3

estimates pollution - 3

recessionary - 3

concentration - 3

industry output - 3

competitor - 3

aging - 3

substitute - 3

endowment - 3

performance - 3

strategic - 3

Viewing papers 151 through 160 of 174


  • Working Paper

    Measuring The Performance Of Government Technology Programs: Lessons From Manufacturing Extension

    December 1997

    Working Paper Number:

    CES-97-18

    Managers of government technology programs are under increasing pressure to demonstrate the effectiveness of their programs. In this paper we examine the issues involved in credibly evaluating such programs in the context of recent efforts to evaluate manufacturing extension programs in the U.S. We provide a stylized model of the dynamic competitive environment in which the plants and firms targeted by these programs operate and discuss its implications for evaluation. We compare and contrast the various methodologies and data sets used to evaluate manufacturing extension. We conclude that the best currently available method for measuring the overall effectiveness of programs such as manufacturing extension is to combine program administrative data with existing panel data sets.
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  • Working Paper

    Productivity Adjustments and Learning-by-Doing as Human Capital

    November 1997

    Authors: Jim Bessen

    Working Paper Number:

    CES-97-17

    This paper measures plant-level productivity gains associated with learning curves across the entire manufacturing sector. We measure these gains at plant startups and also after major employment changes. We find: 1.) The gains are strongly associated with a variety of human capital measures implying that learning-by-doing is largely a firm-specific human capital investment. 2.) This implicit investment is large; many plants invest as much in learning-by-doing as they invest in physical capital and much more than they invest in formal job training. 3.) This investment differs persistently over industries and is higher with greater R&D. 4.) Consistent with a learning-by-doing interpretation, the human capital investment is much larger following employment decreases than increases. We conclude that learning-by-doing is a major factor in wage determination, technical progress and asymmetric employment adjustment costs.
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  • Working Paper

    Output Price And Markup Dispersion In Micro Data: The Roles Of Producer And Heterogeneity And Noise

    August 1997

    Working Paper Number:

    CES-97-10

    This paper provides empirical evidence on the extent of producer heterogeneity in the output market by analyzing output price and price-marginal cost markups at the plant level for thirteen homogeneous manufactured goods. It relies on micro data from the U.S. Census of Manufactures over the 1963-1987 period. The amount of price heterogeneity varies substantially across products. Over time, plant transition patterns indicate more persistence in the pricing of individual plants than would be generated by purely random movements. High-price and low-price plants remain in the same part of the price distribution with high frequency, suggesting that underlying time-invariant structural factors contribute to the price dispersion. For all but two products, large producers have lower output prices. Marginal cost and the markups are estimated for each plant. The markup remains unchanged or increases with plant size for all but four of the products and declining marginal costs play an important role in generating this pattern. The lower production costs for large producers are, at least partially, passed on to purchasers as lower output prices. Plants with the highest and lowest markups tend to remain so over time, although overall the persistence in markups is less than for output price, suggesting a larger role for idiosyncratic shocks in generating markup variation.
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  • Working Paper

    Are We Overstating the Economic Costs of Environmental Protection?

    May 1997

    Working Paper Number:

    CES-97-12

    Reported expenditures for environmental protection in the U.S. are estimated to exceed $150 billion annually or about 2% of GDP. This estimate is often used as an assessment of the burden of current regulatory efforts and a standard against which the associated benefits are measured. This makes it a key statistic in the debate surrounding both current and future environmental regulation. Little is known, however, about how well reported expenditures relate to true economic cost. True economic cost depends on whether reported environmental expenditures generate incidental savings, involve uncounted burdens, or accurately reflect the total cost of environmental protection. This paper explores the relationship between reported expenditures and economic cost in a number of major manufacturing industries. Previous research has suggested that an incremental $1 of reported environmental expenditures increases total production costs by anywhere from $1 to $12, i.e., increases in reported costs probably understate the actual increase in economic cost. Surprisingly, our results suggest the reverse, that increases in reported costs may overstate the actual increase in economic cost. Our results are based a large plant-level data set for eleven four-digit SIC industries. We employ a cost-function modeling approach that involves three basic steps. First, we treat real environmental expenditures as a second output of the plant, reflecting perceived environmental abatement efforts. Second, we model the joint production of conventional output and environmental effort as a cost-minimization problem. Third, we calculate the effect of an incremental dollar of reported environmental expenditures at the plant, industry, and manufacturing sector levels. Our approach differs from previous work with similar data by considering a large number of industries, using a cost-function modeling approach, and paying particular attention to plant-specific effects. Our preferred, fixed-effects model obtains an aggregate estimate of thirteen cents in increased costs for every dollar of reported incremental pollution control expenditures, with a standard error of sixty-one cents. This single estimate, however, conceals the wide range of values observed at the industry and plant level. We also find that estimates using an alternative, random-effects model are uniformly higher. Although the higher, random-effects estimates are more consistent with previous work, we believe they are biased by omitted variables characterizing differences among plants. While further research is needed, our results suggest that previous estimates of the economic cost associated with environmental expenditures have been biased upward and that the possibility of overstatement is quite real. Key words: environmental costs, fixed-effects, translog cost model
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  • Working Paper

    Capital-Energy Substitution Revisted: New Evidence From Micro Data

    April 1997

    Working Paper Number:

    CES-97-04

    We use new micro data for 11,520 plants taken from the Census Bureau=s 1991 Manufacturing Energy Consumption Survey (MECS) and 1991 Annual Survey of Manufactures (ASM) to estimate elasticities of substitution between energy and capital. We found that energy and capital are substitutes. We also found that estimates of Allen elasticities of substitution -- which have been used as a standard measure of substitution -- are sensitive to varying data sets and levels of aggregation. In contrast, estimates of Morishima elasticities of substitution -- which are theoretically superior to the Allen elasticities -- are more robust (except when two-digit level data are used). The results support the views that (i) the Morishima elasticity is a better measure of factor substitution and (ii) micro data provide more accurate elasticity estimates than those obtained from aggregate data. Our findings appear to resolve the long-standing conflict among the estimates reported in the many previous studies regarding energy-capital substitution/complementarity.
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  • Working Paper

    Technology and Jobs: Secular Changes and Cyclical Dynamics

    September 1996

    Working Paper Number:

    CES-96-07

    In this paper, we exploit plant-level data for U.S. manufacturing for the 1970s and 1980s to explore the connections between changes in technology and the structure of employment and wages. We focus on the nonproduction labor share (measured alternatively by employment and wages) as the variable of interest. Our main findings are summarized as follows: (i) aggregate changes in the nonproduction labor share at annual and longer frequencies are dominated by within plant changes; (ii) the distribution of annual within plant changes exhibits a spike at zero, tremendous heterogeneity and fat left and right tails; (iii) within plant secular changes are concentrated in recessions; and (iv) while observable indicators of changes in technology account for a significant fraction of the secular increase in the average nonproduction labor share, unobservable factors account for most of the secular increase, most of the cyclical variation and most of the cross sectional heterogeneity.
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  • Working Paper

    Learning by Doing and Plant Characteristics

    August 1996

    Authors: Ron Jarmin

    Working Paper Number:

    CES-96-05

    Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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  • Working Paper

    Evaluation And Use Of The Pollution Abatement Costs And Expenditures Survey Micro Data

    January 1996

    Working Paper Number:

    CES-96-01

    The Pollution Abatement Costs and Expenditures Survey (PACE) is an annual survey of manufacturing establishment=s operating costs and capital investment expenditures for pollution abatement purposes. This paper provides a description and evaluation of the PACE micro data available at the Center for Economic Studies (CES). The paper provides an overview of the survey, how the sample is drawn, how the survey questionnaire has changed over time, an assessment of the data quality, and suggestions for the use of the data, as well as its limitations. Also included are suggestions for modifying the survey design and data processing procedures. The PACE data series, linked to the economic data in CES= Longitudinal Research Database (LRD), covers the years 1979-1993, excluding 1983 and 1987.
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  • Working Paper

    The Missing Link: Technology, Productivity, and Investment

    October 1995

    Authors: Laura Power

    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
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  • Working Paper

    Technology Locks, Creative Destruction And Non-Convergence In Productivity Levels

    April 1995

    Authors: Douglas W Dwyer

    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.
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