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On Specification and Inference in the Econometrics of Public Procurement




In Paper [I] we use data on Swedish public procurement auctions for internal regular cleaning service contracts to provide novel empirical evidence regarding green public procurement (GPP) and its effect on the potential suppliers’ decision to submit a bid and their probability of being qualified for supplier selection. We find only a weak effect on supplier behavior which suggests that GPP does not live up to its political expectations. However, several environmental criteria appear to be associated with increased complexity, as indicated by the reduced probability of a bid being qualified in the postqualification process. As such, GPP appears to have limited or no potential to function as an environmental policy instrument. In Paper [II] the observation is made that empirical evaluations of the effect of policies transmitted through public procurements on bid sizes are made using linear regressions or by more involved non-linear structural models. The aspiration is typically to determine a marginal effect. Here, I compare marginal effects generated under both types of specifications. I study how a political initiative to make firms less environmentally damaging implemented through public procurement influences Swedish firms’ behavior. The collected evidence brings about a statistically as well as economically significant effect on firms’ bids and costs. Paper [III] embarks by noting that auction theory suggests that as the number of bidders (competition) increases, the sizes of the participants’ bids decrease. An issue in the empirical literature on auctions is which measurement(s) of competition to use. Utilizing a dataset on public procurements containing measurements on both the actual and potential number of bidders I find that a workhorse model of public procurements is best fitted to data using only actual bidders as measurement for competition. Acknowledging that all measurements of competition may be erroneous, I propose an instrumental variable estimator that (given my data) brings about a competition effect bounded by those generated by specifications using the actual and potential number of bidders, respectively. Also, some asymptotic results are provided for non-linear least squares estimators obtained from a dependent variable transformation model. Paper [VI] introduces a novel method to measure bidders’ costs (valuations) in descending (ascending) auctions. Based on two bounded rationality constraints bidders’ costs (valuations) are given an imperfect measurements interpretation robust to behavioral deviations from traditional rationality assumptions. Theory provides no guidance as to the shape of the cost (valuation) distributions while empirical evidence suggests them to be positively skew. Consequently, a flexible distribution is employed in an imperfect measurements framework. An illustration of the proposed method on Swedish public procurement data is provided along with a comparison to a traditional Bayesian Nash Equilibrium approach.

Suggested Citation

  • Sundström, David, 2016. "On Specification and Inference in the Econometrics of Public Procurement," Umeå Economic Studies 931, Umeå University, Department of Economics.
  • Handle: RePEc:hhs:umnees:0931

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    References listed on IDEAS

    1. Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2000. "Optimal Nonparametric Estimation of First-Price Auctions," Econometrica, Econometric Society, vol. 68(3), pages 525-574, May.
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    5. Paarsch, Harry J., 1992. "Deciding between the common and private value paradigms in empirical models of auctions," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 191-215.
    6. Mark B. Stewart, 1983. "On Least Squares Estimation when the Dependent Variable is Grouped," Review of Economic Studies, Oxford University Press, vol. 50(4), pages 737-753.
    7. Leonardo Rezende, 2008. "Econometrics of auctions by least squares," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(7), pages 925-948.
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    13. William Vickrey, 1961. "Counterspeculation, Auctions, And Competitive Sealed Tenders," Journal of Finance, American Finance Association, vol. 16(1), pages 8-37, March.
    14. Harry J. Paarsch & Han Hong, 2006. "An Introduction to the Structural Econometrics of Auction Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262162350, March.
    15. John C. Harsanyi, 1967. "Games with Incomplete Information Played by "Bayesian" Players, I-III Part I. The Basic Model," Management Science, INFORMS, vol. 14(3), pages 159-182, November.
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    More about this item


    auctions; dependent variable transformation model; green public procurement; indirect inference; instrumental variable; latent variable; log-generalized gamma distribution; maximum likelihood; measurement error; non-linear least squares; objective effectiveness; orthogonal polynomial regression; prediction; simulation estimation; structural estimation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • H57 - Public Economics - - National Government Expenditures and Related Policies - - - Procurement
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy

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