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Revenue Forecasting in Low-Income and Developing Countries: Biases and Potential Remedies

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Abstract

This chapter surveys the revenue forecasting landscape in middle- and low-income countries, with a focus on examining the existence of forecast bias and potential remedial reforms. After reviewing the scarce literature on revenue forecast bias, we construct a new dataset of ex-ante revenue forecasts and ex-post realizations for 26 countries using the information from the Public Expenditure and Financial Accountability (PEFA) reports. An analysis of forecast errors reveals that most of these countries tend to overestimate their revenues. Also, the magnitude of forecast errors is significantly large and appears to be correlated with the measures of income and administrative capacity. The chapter then reviews the experience of two institutional innovations for improving the budget process and forecasts: semi-autonomous revenue authorities (SARAs) and independent fiscal councils. The evidence on the effectiveness of the former in increasing tax-to-GDP ratios remains mixed, whereas the latter is a relatively new institution whose future trajectory is still unknown in most of the low-income countries. Although neither of these institutions has been explicitly tasked with providing independent revenue forecasts that could address the bias observed in our sample, both of them could directly and indirectly contribute. Lastly, the chapter highlights the lack of research and data on revenue forecasting in low- and middle-income countries and identifies avenues for future research.

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Notes

  1. 1.

    Financing for Development, Addis Ababa, July 13–15, 2017. Countries agreed to an array of measures aimed at widening the revenue base, improving tax collection, and combating tax evasion and illicit financial flows.

  2. 2.

    First Global Conference of the Platform for Collaboration on Tax—Taxation and the Sustainable Development Goals, New York, February 14–16, 2018.

  3. 3.

    The PCT is a 2016 joint initiative of the International Monetary Fund (IMF), Organization for Economic Co-operation and Development (OECD), United nations, and the World to strengthen collaboration on DRM. The four PCT partners support country efforts through policy dialogue and capacity building. In this context, the PCT has developed the Medium-Term Revenue Strategy (MTRS) as an approach for coordinated and sustained support to comprehensive country-led tax reform.

  4. 4.

    The concept of the MTRS was introduced in Enhancing the Effectiveness of External Support in Building Tax Capacity in Developing Countries, Platform for Collaboration on Tax (IMF, OECD, UN, and WB), July 2016, available at https://www.imf.org/external/np/pp/eng/2016/072016.pdf. A further concept note develops its main components and illustrates the nature of an MTRS document in an appendix. In all this documentation, the need to strengthen revenue forecasting and address potential biases is hardly mentioned.

  5. 5.

    Named after the German economist Adolph Wagner, the principle states that as nations develop their public sector grow to provide for welfare functions, social activities, and protective actions.

  6. 6.

    These are resources such as budgets which can be subject to overuse when different groups have conflicting interests, giving rise to what has become known as the “tragedy of the commons,” whereby individual pursuing their self-interest behave contrary to the common good (Weingast et al. 1981).

  7. 7.

    Time inconsistency refers to the changing of decision makers’ preferences over time (Kydland and Prescott 1977). The deficit (and debt) bias has also been analyzed and explained in a game theory framework such as the prisoners’ dilemma (Hallerberg and von Hagen 1997) or principal-agent relationships (Dixit et al. 1997).

  8. 8.

    Fiscal space is defined as the “room in a government’s budget that allows it to provide resources for a desired purpose without jeopardizing the sustainability of its financial position or the stability of the economy.” See Heller (2005).

  9. 9.

    PEFA is a program that was founded in 2001 as a multi-donor partnership between the European Commission, the IMF, the World Bank, the French Ministry of Foreign and European Affairs, the Norwegian Ministry of Foreign Affairs, the Swiss State Secretariat for Economic Affairs, and the U.K.’s Department for International Development. See www.pefa.org.

  10. 10.

    This approach is, thus, different from Danninger et al. (2005) where the focus is on political interference defined as “a significant deviation between the budget forecast and a forecast by technical experts.”

  11. 11.

    Under the HIPC initiative and the related Multilateral Debt Relief Initiative (MDRI), countries eligible for debt relief (decision point) may eventually graduate from the initiative (completion point) so that the debt relief is granted and they can re-access international market for their borrowing. So far, 36 countries (30 of which are in Africa) for a total of US$99 billion worth of debt relief have graduated.

  12. 12.

    According to a 2018 IMF report, debt burdens and vulnerabilities have risen significantly since 2013 in low-income developing countries (LIDCs) reflecting a mix of factors including exogenous shocks and loose fiscal policies. While the majority of LIDCs remain at low or moderate risk of debt distress, the number of countries at high risk or in debt distress has increased from 13 in 2013 to 24 in January 2018. See IMF 2018, Macroeconomic Developments and Prospects in Low-Income Developing Countries.

  13. 13.

    The word “institution” is here defined, along with Douglas North (1991), as “both informal constraints (sanctions, taboos, customs, traditions, and codes of conduct), and formal rules (constitutions, laws, property rights).”

  14. 14.

    The Monitoring of Fund Arrangements (MONA) database contains comparable information on the economic objectives and outcomes in fund-supported arrangements. It tracks the performance of countries in terms of scheduled purchases and reviews, quantitative and structural conditionality, and macroeconomic indicators. The database is accessible at https://www.imf.org/external/np/pdr/mona/index.aspx.

  15. 15.

    Our selection criteria have the following parameters: Status of the report (final), study type (national), assessment framework (2016), and finally we use the reports that are publicly available and have undergone PEFA check. Based on this criterion, we obtained information for 26 countries in October 2018. The sample is substantially representative of the Global South and includes countries from Latin America, West and East Africa, the Middle East, and South and East Asia.

  16. 16.

    Iraq’s parliament did not adopt a budget in the FY2014, so the budget information is not available and leads to a corresponding loss of one country year.

  17. 17.

    The literature on state capacity finds strong correlation between GDP and various measures of bureaucratic and administrative capacity. However, the direction of the effect is controversial since institutions are often considered endogenous (see, e.g., Hendrix 2010; Cingolani 2013).

  18. 18.

    We use 2014 values of GDP since that serves as the mid-point of our sample years (FY2012–FY2017).

  19. 19.

    World Bank’s Income Classification of Countries, 2018 https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups.

  20. 20.

    Another aspect that deserves more investigation is the presence of a financial arrangement with the IMF. Out of our sample, 14 countries had various financial arrangements with the IMF. The a priori would be that because of the catalytic role of an IMF arrangement and the related conditionality, IFIs and bilateral donors may induce an optimistic bias on macroeconomic and fiscal forecasts. A cursory analysis however does not seem to support the a priori: of the countries showing the largest MAPFE in Fig. 5.4 only two (Madagascar and Niger) had active financial arrangements with the IMF during the observed period.

  21. 21.

    Based on the IMF Fiscal Rules database https://www.imf.org/external/datamapper/fiscalrules/map/map.htm, as of 2015 only 14 countries had adopted some form of revenue rules, with 8 of them being LDCs under the West Africa Economic and Monetary Union (WAEMU).

  22. 22.

    As discussed in Schaechter et al. (2012), “revenue rules set ceilings or floors on revenues and are aimed at boosting revenue collection and/or preventing an excessive tax burden (or both). … but setting ceilings or floors on revenues can be challenging as revenues maybe have large cyclical component … Exceptions are those rules that restrict the use of windfall revenue for additional spending. Revenue rules alone could also result in procyclical fiscal policy, as floors do not generally account for the operation of automatic stabilizers.”

  23. 23.

    Reviewing the rationale as well as the experience of agencification is beyond the purpose of this chapter. There is a vast literature that has emerged over the last two decades. A good place to start is Pollitt and Talbot (2003).

  24. 24.

    Whereas according to Dom (2018) this is a “minimal definition,” it allows comparing SARAs’ performance with that of conventional tax administrations. Roel also emphasizes that “while they share many elements, there is variation in the nature of SARAs with respect to their competences, organizational set-up, and responsibilities.”

  25. 25.

    According to the IMF Fiscal Council Dataset available at https://www.imf.org/external/np/fad/council/, out of the existing 39 IFCs as of end-2017, about two-thirds are in Europe; only two LDCs—Kenya and Uganda—have established IFCs in the form of Parliamentary Budget Offices, as is the case for South Africa. For a description of the data set, seeIMF (2013) and Debrun, X, X. Zhang, and V. Lledó. 2017. “The Fiscal Council Dataset: A Primer to the 2016 Vintage,” Background Paper available at http://www.imf.org/external/np/fad/council/.

  26. 26.

    In 2014, the OECD adopted 22 principles codifying best practices for well-designed IFCs: OECD 2014, Recommendation of the Council on Principles for Independent Fiscal Institutions, adopted on February 13, 2014.

  27. 27.

    Since its first edition issues in 1998, the IMF fiscal transparency code and its subsequent revisions—the most recent of which is dated 2014—have always identified among its principles the need for fiscal information to be externally scrutinized by “a national audit body or an equivalent organization that is independent of the executive.” The most recent version states in its pillar 2 Fiscal Forecasting and Budgeting under Budget Credibility that (principle 2.4.1 Independent Evaluation) “the government’s economic and fiscal forecasts and performance are subject to independent evaluation.” See also the IMF Fiscal Transparency Manual, 2018, pp. 84–88.

  28. 28.

    Two other key functions—interactions with shareholder and monitoring compliance with fiscal rules where they are in place—while important have a less direct bearing on the scope of this chapter. Of the 39 IFCs describe in the IMF dataset, the most common functions identified are the assessment of government budgetary and fiscal performance in relation to fiscal objectives and strategic priorities (31), forecast assessment (30), monitoring of fiscal rules (28), performing normative analysis or providing recommendations (27), and assessing long-term sustainability (25). Less common are the costing of policy measures (16) and forecast preparation (17), as reported by Wehner (2018), in Beetsma and Debrun (2018).

  29. 29.

    Kenya, Fiscal transparency Evaluation, IMF Country Report No. 16/221, June.

  30. 30.

    Uganda, Fiscal transparency Evaluation, IMF Country Report No. 17/130, May.

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Cangiano, M., Pathak, R. (2019). Revenue Forecasting in Low-Income and Developing Countries: Biases and Potential Remedies. In: Williams, D., Calabrese, T. (eds) The Palgrave Handbook of Government Budget Forecasting. Palgrave Studies in Public Debt, Spending, and Revenue. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-18195-6_5

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