IDEAS home Printed from https://ideas.repec.org/a/url/upravl/v12y2021i2p46-62.html
   My bibliography  Save this article

Targeted programs in the Russian Federation as a matter for evaluation

Author

Listed:
  • Vitaly L. Tambovtsev

    (Lomonosov Moscow State University, Moscow, Russia)

Abstract

The article deals with the issues of targeted programs’ efficiency evaluation in the state budgeting. Targeted programs play a significant role in both the public and private sectors of the economy all over the world, and the problems of their assessment, including the efficiency evaluation, are widely discussed in the scientific literature. At the same time, the concepts within such programs and efficiency evaluation are rather diverse, which makes it difficult to form a set of reliable methods that would (1) meet the needs of decision-makers, (2) have a scientific validity, and (3) be relevant and add to the welfare of the country’s population. Such assessments can best enhance the efficiency of the use of budgetary resources. Behavioral decision theory, measurement and estimation theories and system analysis constitute the methodological basis of the study. The current research delves into the fundamental concepts used while evaluating targeted programs and compares their theoretical provisions with the practical aspects of application. We find that the existing interpretation of the terms “program” and “efficiency” exercised in Russia does not allow realizing the full potential of targeted programs as tools of planning when it comes to enhancing the efficiency of budget expenditures incurred in resolving complex socio-economic problems. In addition, this interpretation impedes the monitoring of planned events inherent in the methods and models of program evaluation adopted overseas. The theoretical and practical significance of the study lies in the substantiation and development of particular practices aimed at evaluating public programs in Russia.

Suggested Citation

  • Vitaly L. Tambovtsev, 2021. "Targeted programs in the Russian Federation as a matter for evaluation," Upravlenets, Ural State University of Economics, vol. 12(2), pages 46-62, April.
  • Handle: RePEc:url:upravl:v:12:y:2021:i:2:p:46-62
    DOI: 10.29141/2218-5003-2021-12-2-4
    as

    Download full text from publisher

    File URL: http://upravlenets.usue.ru/images/90/4.pdf
    Download Restriction: no

    File URL: http://upravlenets.usue.ru/en/issues-2021/796
    Download Restriction: no

    File URL: https://libkey.io/10.29141/2218-5003-2021-12-2-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Rhys Andrews & Tom Entwistle, 2013. "Four Faces of Public Service Efficiency," Public Management Review, Taylor & Francis Journals, vol. 15(2), pages 246-264, February.
    2. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    3. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    4. Ann Langley & Henry Mintzberg & Patricia Pitcher & Elizabeth Posada & Jan Saint-Macary, 1995. "Opening up Decision Making: The View from the Black Stool," Organization Science, INFORMS, vol. 6(3), pages 260-279, June.
    5. Gresser, Klaus, 1973. "Application of ppbs to r&d planning," Research Policy, Elsevier, vol. 2(1), pages 40-55, April.
    6. Novick, David, 1969. "Long-range planning through program budgeting : A better way to allocate resources," Business Horizons, Elsevier, vol. 12(1), pages 59-65, February.
    7. Haridimos Tsoukas, 2017. "Don't Simplify, Complexify: From Disjunctive to Conjunctive Theorizing in Organization and Management Studies," Journal of Management Studies, Wiley Blackwell, vol. 54(2), pages 132-153, March.
    8. Daniel Kahneman & Jack L. Knetsch & Richard H. Thaler, 1991. "Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 193-206, Winter.
    9. Hitch, Charles J., 1969. "What are the programs in planning, programming, budgeting?," Socio-Economic Planning Sciences, Elsevier, vol. 2(2-4), pages 465-472, April.
    10. Luis Rayo & Gary S. Becker, 2007. "Evolutionary Efficiency and Happiness," Journal of Political Economy, University of Chicago Press, vol. 115, pages 302-337.
    11. Stefan Mann & Henry Wüstemann, 2010. "Efficiency and utility: an evolutionary perspective," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 37(9), pages 676-685, August.
    12. Laure Cabantous & Jean-Pascal Gond, 2011. "Rational Decision Making as Performative Praxis: Explaining Rationality's Éternel Retour," Organization Science, INFORMS, vol. 22(3), pages 573-586, June.
    13. Patrick J. Devlin, 2010. "Exploring efficiency's dominance: the wholeness of the process," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 7(2), pages 141-162, June.
    14. V. Tambovtsev & I. Rozhdestvenskaya., 2016. "Program-target planning: Yesterday, today… Tomorrow?," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 6.
    15. María-Isabel Encinar, 2016. "Evolutionary efficiency in economic systems: A proposal," Cuadernos de Economía - Spanish Journal of Economics and Finance, Asociación Cuadernos de Economía, vol. 39(110), pages 93-98, Mayo.
    16. Dina Pomeranz, 2017. "Impact Evaluation Methods in Public Economics," Public Finance Review, , vol. 45(1), pages 10-43, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    2. Manuel Arellano & Stéphane Bonhomme, 2017. "Quantile Selection Models With an Application to Understanding Changes in Wage Inequality," Econometrica, Econometric Society, vol. 85, pages 1-28, January.
    3. Andrew Chesher & Adam M. Rosen, 2021. "Counterfactual Worlds," Annals of Economics and Statistics, GENES, issue 142, pages 311-335.
    4. James J. Heckman, 2008. "Econometric Causality," International Statistical Review, International Statistical Institute, vol. 76(1), pages 1-27, April.
    5. Sakos, Grayson & Cerulli, Giovanni & Garbero, Alessandra, 2021. "Beyond the ATE: Idiosyncratic Effect Estimation to Uncover Distributional Impacts Results from 17 Impact Evaluations," 2021 Annual Meeting, August 1-3, Austin, Texas 314017, Agricultural and Applied Economics Association.
    6. Wu, Ximing & Perloff, Jeffrey M., 2007. "Information-Theoretic Deconvolution Approximation of Treatment Effect Distribution," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6bm6n30x, Department of Agricultural & Resource Economics, UC Berkeley.
    7. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    8. Cunha, Flavio & Heckman, James, 2008. "A New Framework For The Analysis Of Inequality," Macroeconomic Dynamics, Cambridge University Press, vol. 12(S2), pages 315-354, September.
    9. Michael Grothe-Hammer & Héloïse Berkowitz & Olivier Berthod, 2022. "Decisional organization theory: towards an integrated framework of organization," Post-Print hal-03699112, HAL.
    10. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    11. Pereda-Fernández, Santiago, 2023. "Identification and estimation of triangular models with a binary treatment," Journal of Econometrics, Elsevier, vol. 234(2), pages 585-623.
    12. Richard Blundell & Amanda Gosling & Hidehiko Ichimura & Costas Meghir, 2007. "Changes in the Distribution of Male and Female Wages Accounting for Employment Composition Using Bounds," Econometrica, Econometric Society, vol. 75(2), pages 323-363, March.
    13. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
    14. Kasy, Maximilian, "undated". "Instrumental variables with unrestricted heterogeneity and continuous treatment - DON'T CITE! SEE ERRATUM BELOW," Working Paper 33257, Harvard University OpenScholar.
    15. Peter Z. Schochet, "undated". "Is Regression Adjustment Supported by the Neyman Model for Causal Inference? (Presentation)," Mathematica Policy Research Reports abfc39d59c714499b2fe42f68, Mathematica Policy Research.
    16. Kitagawa, Toru, 2021. "The identification region of the potential outcome distributions under instrument independence," Journal of Econometrics, Elsevier, vol. 225(2), pages 231-253.
    17. Flavio Cunha & James Heckman & Salvador Navarro, 2005. "Separating uncertainty from heterogeneity in life cycle earnings," Oxford Economic Papers, Oxford University Press, vol. 57(2), pages 191-261, April.
    18. Steven F. Lehrer & R. Vincent Pohl & Kyungchul Song, 2022. "Multiple Testing and the Distributional Effects of Accountability Incentives in Education," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1552-1568, October.
    19. Philipp Eisenhauer & James J. Heckman & Edward Vytlacil, 2015. "The Generalized Roy Model and the Cost-Benefit Analysis of Social Programs," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 413-443.
    20. Sylvain Chassang & Gerard Padro I Miquel & Erik Snowberg, 2012. "Selective Trials: A Principal-Agent Approach to Randomized Controlled Experiments," American Economic Review, American Economic Association, vol. 102(4), pages 1279-1309, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:url:upravl:v:12:y:2021:i:2:p:46-62. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Victor Blaginin (email available below). General contact details of provider: https://edirc.repec.org/data/usueeru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.