The Guide has been prepared to assist economies that participate or are considering participating in the Coordinated Direct Investment Survey (CDIS). The Guide is also intended to assist economies already participating in the CDIS by providing statistical guidelines that compilers may find useful for improving the quality of their direct investment data. It updates the CDIS Guide that was released in 2010 to incorporate clarifications based on the International Monetary Fund’s (IMF’s) experience in conducting the CDIS and in preparing the Balance of Payments and International Investment Position Compilation Guide (BPM6 CG). This chapter covers the purpose, background, and strategy adopted for the implementation of the CDIS, and an overview on how the Guide is organized.
Direct investment arises when a unit resident in one economy makes an investment that gives control1 or a significant degree of influence on the management of an enterprise that is resident in another economy. This concept is operationalized where a direct investor (DI) owns equity that entitles it to 10 percent2 or more of the voting power3 in the direct investment enterprise (DIENT) (which is usually equal to ownership of ordinary shares). Once that threshold has been reached, the units involved are said to be in a direct investment relationship, and the equity and debt instrument positions between the DI and the DIENT, and between all DIENTs of the same DI, are included in direct investment, except for debt between selected affiliated financial corporations.4 Included in direct investment are units that are under the control or influence of the same immediate or indirect investor, but do not have control or significant influence over one another. These units are known as “fellow enterprises.” Data in the CDIS are recorded by economy based on the location of the immediate counterpart economy relative to a direct investment position.
This chapter first defines equity and investment fund shares, and debt instruments, and then explains the valuation methods to be used when requesting data on direct investment positions. As well, a brief introduction to the model survey forms is provided.
The purpose of this chapter is to assist compilers in improving the quality of direct investment data by using some recommended self-assessment tools for compiling and reporting data, by assessing consistency between International Investment Position (IIP) and CDIS data, and by assessing data reported by counterpart economies (mirror data).
This Coordinated Direct Investment Survey Guide (Guide) has been prepared to assist economies in participating in the Coordinated Direct Investment Survey (CDIS). The CDIS is being conducted under the auspices of the Statistics Department of the IMF across a wide range of economies. The survey is conducted simultaneously by all participating economies; uses consistent definitions; and encourages best practices in collecting, compiling, and disseminating data on direct investment positions. The CDIS is thus an important tool in capturing world totals and the geographic distribution of direct investment positions, thereby contributing to important new understandings of the extent of globalization, and improving the overall quality of direct investment data worldwide. As of the writing of this updated Guide, more than 100 economies participate in the CDIS.
Daniel Gurara, Mr. Vladimir Klyuev, Miss Nkunde Mwase, Mr. Andrea F Presbitero, Xin Cindy Xu, and Mr. Geoffrey J Bannister
This paper examines trends in infrastructure investment and its financing in low-income developing countries (LIDCs). Following an acceleration of public investment over the last 15 years, the stock of infrastructure assets increased in LIDCs, even though large gaps remain compared to emerging markets. Infrastructure in LIDCs is largely provided by the public sector; private participation is mostly channeled through Public-Private Partnerships. Grants and concessional loans are an essential source of infrastructure funding in LIDCs, while the complementary role of bank lending is still limited to a few countries. Bridging infrastructure gaps would require a broad set of actions to improve the efficiency of public spending, mobilize domestic resources and support from development partners, and crowd in the private sector.
I regress real GDP growth rates on the IMF’s growth forecasts and find that IMF forecasts behave similarly to those generated by overfitted models, placing too much weight on observable predictors and underestimating the forces of mean reversion. I identify several such variables that explain forecasts well but are not predictors of actual growth. I show that, at long horizons, IMF forecasts are little better than a forecasting rule that uses no information other than the historical global sample average growth rate (i.e., a constant). Given the large noise component in forecasts, particularly at longer horizons, the paper calls into question the usefulness of judgment-based medium and long-run forecasts for policy analysis, including for debt sustainability assessments, and points to statistical methods to improve forecast accuracy by taking into account the risk of overfitting.
This paper concludes that the existing framework remains broadly appropriate, but proposes methodological refinements to improve the assessment of market access, clarifies how serious short-term vulnerabilities are assessed, and proposes a modest extension of the transition period before graduation decisions become effective.