The current account includes trade in goods and services; income on assets (such as rents, interest, profits and dividends); and current transfer payments (including foreign aid, government subscriptions to international organizations, pension payments to workers living abroad, and foreign worker remittances to their home countries). The larger of these elements have representation in IFs.
The capital account involves changes in ownership of assets, such as includes foreign direct investment (FDI), portfolio flows, IMF credits and World Bank loans, net bank lending, other net flows, and change in reserves. Note that these capital account related flows have associated stocks (assets) of importance in understanding their own long-term behavior and that of the larger financial system including the current account.
With respect to the elements of the current and capital accounts, another part of this documentation (part of the representation of goods and services and their balances) has explained trade. This section will discuss foreign aid and worker remittances, two additional elements of the current account, then move to FDI and portfolio flows, two critical elements of the capital account. It will then move to flows from and to international financial institutions, which are also placed in the capital account. A subsequent section on overall equilibration will also address changes in reserves, which are strictly speaking also part of the broader capital account.
IFs uses a "pool" approach to aid (AID) rather than indicating bilateral flows from particular donors to particular recipients. That is, all aid from all donors flows into the pool and then all recipients draw proportions of the pool.
IFs uses the aid value parameter ( aiddon ) to calculate the aid (AID) from donors and aidrec to calculate the targeted aid to recipients. The pool of aid donations determines the actual total level of interstate aid flows, however, and is allocated among potential recipients according to the proportions targeted for each.
Aid outflows are negative and the total aid pool given (AIDP) is the sum of the negative flows, while the total desired aid of recipients (AIDR) is the sum of positive flows.
A re-computation of aid for recipients distributes the aid pool across their demands.
Worker remittances are tied closely to the migration formulation of the IFs demographic model (see the documentation of that model). It is important to know the number of foreign workers from each country and into each country (POPFOREIGN), as well as the pattern of remittances per worker, as a basis for computing remittance levels. The IFs migration module once relied heavily on UN data for past migration levels and also tapped their near-term forecasts. The IFs preprocessor and model now rely primarily on migration data from the International Institute of Applied Systems Analysis (IIASA). The preprocessor has fairly extensive algorithms to reconcile that migration data with remittance data, and migration and remittance data from the World Development Indicators with foreign population data (from the same source).
The data do not, however, exist for global representation of dyadic remittance flows that is, of flows from country of origin to country of destination. IFs therefore uses a pooled approach, representing aggregate flows out of countries and aggregate flows into countries, requiring that they be balanced, but not attempting to trace dyadic patterns. The pooled approach is also used by IFs in trade (where dyadic representation would be possible), foreign aid (where it would be difficult but not completely impossible to obtain dyadic data), and other financial flows (where again dyadic data are seldom available).
The specific formulation computes a global average remittance rate per worker (WWorkRemitRate) and a host-country specific ratio of remittance rate to the global one (WorkRemitRate) in the first year. In subsequent years, those rates are applied to the number of foreign workers, but adjusted by the ratio of current GDP per capita to initial GDP per capita. The outflows are assigned to inflow countries so as to maintain a global balance.
Initial data on worker remittances, added to the IFs database as a percentage of GDP, come from the World Bank’s WDI, as do data on foreign population as a percentage of the total. The original sources were Global Development Finance and the OECD, respectively. At one time the worker remittance series only included data by country of receipt, forcing us to estimate remittances by countries of origin in the preprocessor on the basis of the foreign worker series. Now remittance flows in and out are reported, but there are still balancing issues.
Foreign Direct Investment
Firms are primarily in charge on both ends of foreign direct investment. In general, of course, the pattern is likely to be that firms direct FDI from relatively capital-rich countries to relatively capital-poor ones. Estimation reinforces that presumption by showing the patterns found in the IFs database (using FDI flow data from WDI). A less steeply sloped line is the relationship between GDP per capita at PPP and the stocks of FDI inflows as a ratio to GDP. A more steeply sloped line is the relationship between GDP per capita at PPP and the stocks of FDI outflows as a ratio to GDP. Both lines are upward sloping and, in fact, countries are simultaneously larger sources and targets of investment, even relative to GDP, as they develop. Yet, roughly speaking, countries are net recipients until GDP per capita is somewhat above $20,000 and net sources thereafter.
IFs recognizes that these patterns will not be universal. Thus the algorithm that determines stocks of investment outflows is one that builds in the historic pattern of FDI outflows, but that assumes convergence over long periods of time, such as a century, towards the generic pattern. The same is true for recipients and stocks of inflows. It would probably be reasonable to posit that both lines would shift to the right over time as the average per capita levels of global GDP increase. We have not built that presumption into the model at this time.
In addition to the relative behavior of firms in states across the system, another behavioral issue is the overall pattern of increase or decrease in FDI flows relative to the size of the global economy. Over the last several decades FDI has grown steadily as a portion of the global capital stock and global economy. Economic historians are, however, quick to point out that the turn of the 20th century was a period of enhanced globalization of capital and that those flows then retreated for most of the 20th century before advancing again. And this century has already seen some at least temporary retreats. Thus the base case presumption built into IFs, based roughly on patterns of the late 1990s, is of growth in FDI flows at a rate that exceeds economic growth but that convergences towards GDP growth by 2010.
The representation of FDI in IFs builds from the concepts and general theory around FDI stocks that estimation and the preceding discussion suggest. In each time cycle the model computes stocks of both inflows and outflows. As a first step, the expected stocks of inflows (EXFDISTOCK) are a fraction of GDP (FDIRatio), where the ratio gradually converges from the initial condition for each country (XFDIGDPIn) to the pattern of global ratios expected as a function of GDP (ExpFDIRatioIn).
Exactly the same logic applies to expected stocks of outflows (EXFDISTOUT).
Without further modification, the above formulations would result in stocks that fully determined the annual inflows and outflows. There are, however, empirical initial conditions for such annual flows that should not be ignored, especially in the early years of forecasts; the late 1990s were, for instance, a period of high flow rates that would not be captured by the above formulations.
Thus the formulation has a second step built around flows. Based on the above-expected stocks of FDI inflows (EXFDISTOCK), actual stocks (XFDISTOCK) are computed using a rate of growth (FDIRIn). The user can further intervene in the stock specification with a multiplier ( xfdistockm ). The rate of FDI stock growth converges from an initial rate tied to empirical inflows to an exogenous rate ( xfdistockr ).
Again the logic is the same for outward flows and stocks.
There is, therefore, in the formulation a tension between the convergence of stock patterns to the analytic function for stocks as a portion of GDP and the convergence of them towards growth as specified in the exogenous parameter for rate of stock growth ( xfdistockr ). If the model user were to set the exogenous parameter for all geographical units and time points to approximately the rate of global economic growth, the tension would be resolved. Many users will, however, want to override the analytic specification by using that exogenous parameter.
There is one additional element of the formulation for FDI, which is primarily in place for the purpose of model use in scenarios. It will often be desirable for a user to be able to simply specify a rate of global growth in FDI (including potentially sharp retrenchments in FDI) and impose the resulting global FDI levels (WFDI) on the above formulations, letting the above equations determine country/regional stocks and flows within the global constraint. This formulation element uses a rate of growth (WFDIR) in the ratio of FDI to world GDP (WFDIRGDP) that is set to move from the initially calculated growth rate (WFDIFRI) of world foreign direct investment relative to GDP growth to 0.5% (now WFDIGR) over the first 20 years of the model run. The calculation takes into account the expected depreciation rate of the FDI stock as represented by the lifetime of manufacturing capital ( lks ). The user has some control over this global growth pattern in the form of a multiplier on global FDI ( wfdiwgrm ). Once WFDI is determined, it is used to normalize the country/regional calculations of stocks (XFDISTOCK and XFDISTOUT)—normalization not shown in the equations.
The changes in the ultimate values of stocks, of course, then provide gross inflows and outflows.
Obtaining data for initialization of the stocks and flows of FDI posed some challenges. UNCTAD’s annual World Investment Report had some data on stocks, but they proved difficult to obtain electronically. We therefore turned once again to the World Development Indicators, in spite of the fact that the source provides only flows. It does, however, basically provide both net inflows and net outflows (XFDIFIN and XFDIFOUT). Because of the instability in these numbers over time, the last five years of data were averaged to compute initial conditions for annual flows in the model.
Integrating the flows from 1970, on the assumption that there was relatively little FDI prior to 1970, provided estimates of stocks that seemed fairly reasonable when checked against some of the UNCTAD stock data. But because these do not necessarily yield the same totals for global inflows and outflows, the two sets of numbers were summed for their respective totals, true values were assumed to be the average, and inflows and outflows were normalized to that average. The result was initialization of FDI stocks from abroad (XFDISTOCK) and FDI stocks held abroad (XFDISTOUT).
The algorithm behind portfolio flows, again involving firms in large part but also introducing behavior of households, is essentially the same as that for FDI. And again, model users can intervene to change either systemic growth of portfolio flows or individual country/region patterns.
With respect to portfolio investment, WDI provides flow data on both bond and equity investment. Again averages of the most recent five years were used to compute initial conditions for annual flows, and annual flow data were integrated from 1970 to obtain estimates of portfolio stocks held in developing countries (XPORTFOLIO). Unfortunately, the WDI provided only flows into developing countries and the data fail to account for the source of the flows. Therefore the asset balances were assigned by GDP weight in the preprocessor to developed countries (XPORTSTOUT).
In each time cycle the model computes stocks of both inflows and outflows. As a first step, the expected stocks of inflows (EXPORTFOLIO) are a fraction of GDP (PortfolioRatio), where the ratio gradually converges from the initial condition for each country (XPORTGDPIn) to the pattern of global ratios expected as a function of GDP (ExpPortRatioComp).
Without further modification, the above formulations would result in stocks that fully determined the annual inflows. There are, however, empirical initial conditions for such annual flows that should not be ignored, especially in the early years of forecasts; the late 1990s were, for instance, a period of high flow rates that would not be captured by the above formulations.
Thus the formulation has a second step built around flows. Based on the above-expected stocks of portfolio inflows (EXPorfolio), actual stocks (XPORTFOLIO) are computed using a rate of growth (PortfolioRIn). The user can further intervene in the stock specification with a multiplier ( xportfoliom ). The rate of portfolio stock growth converges from an initial rate tied to empirical inflows to an exogenous rate ( xportr ).
The same logic applies to portfolio outflows, starting with a computation of expected flows.
The expected flows out can then be modified to make them more compatible with initial data and user interventions.
The world sums of stocks for portfolio inflows and outflows will not be identical. IFs computes a world total of flows (WPortfolio) as a step towards imposing it on both.
After the logic of the stock-driven formulation is played out, the final determination of flows is identical to that for FDI except that there is no physical depreciation around portfolio investment.
Ideally foreign direct investment and portfolio investment would be responsive to equilibrating mechanisms. In reality, that is not always the case. FDI and portfolio flows can be, in fact, somewhat perverse, moving from fear or greed in opposite directions to the needed balances. At this point, no linkages of any kind have been added to these flows from exchange rates, liquidity levels, or other elements of the equilibrating mechanisms to be discussed later.
Also, at this point there is no representation of dynamics for direct firm borrowing and lending across country borders. Instead there is a simple growth equation for net external debt. At the least, this equation should be parameterized for user intervention.
International financial institution flows
The international financial institutions (IFIs) are agents of importance for countries around the world. This section explains a basic agent representation of the World Bank and a less-fully elaboration representation of the IMF.
With respect to World Bank agency, the formulations of IFs fall generally into four basic decision categories: How much to loan? To whom to loan? For what purposes to loan? At what terms to loan?
Concerning the total that the bank has to loan at any given time (XWBLOANSTOT), that is a simple sum of lending capacity last year plus repayments (XWBLnRepayTot), minus new loans (XWBLnNewTot), and plus new subscriptions (XWBLnNewSubTot), the last term modified by the loan to equity ratio maintained by the Bank ( xwblneqr ). Repayments or the flows out of countries to the Bank (XWBLNFOUT) depend on total lending to the countries (XWBLOANS), the real interest rates charged by the Bank ( wblintr ) and the repayment rates in years ( xwblnrepr ).
The World Bank and its member countries collectively determine the rates of growth in new subscriptions (XWBSUBF), but we represent that with an exogenous parameter ( xwbloanr ). IFs does not attempt to maintain cohorts of loans to different countries. Nor does IFs track the administrative overhead of the Bank, which could significantly reduce lending capacity over time.
With respect to the countries to which it lends, IFs focuses primarily on determining flows as a percentage of GDP. This is different than the approach to representing FDI or portfolio investment in part because those representations were general with respect to agency. In the case of World Bank lending, there is much reason to believe that it does target flows based on characteristics of the borrowing country. Estimations show three characteristics that demonstrate correlations with annual lending by the Bank as a portion of GDP: GDP per capita (PPP), the Gini coefficient of inequality, and aid that countries receive as official development assistance (ODA) from countries. A more extensive analysis is documented elsewhere (Hughes and Hossain 2003). For instance, GDP per capita and the Human Development Index (HDI) are close substitutes in correlations with Bank lending. After extensive exploration, it was decided to add to IFs a three-variable representation of Bank decision-making concerning the countries to whom it lends.
The function detailed above provides the foundation for a three-step representation of the country-specific lending flows from the bank (XWBLNFIN). The first step is to compute a base value for flows to each country, simply by scaling up each country’s initial lending receipts by the growth in total World Bank lending. Computing such a base is valuable because it preserves the bases for lending that are not captured in the predictive formulation (the three variables capture about three-fourths of the bases).
The second step is to compute an adjusted forecast of lending, taking into account the changes in the predictive factors from initial values. The adjusting factors come into the equation as a ratio of the purely predicted lending rate in the current time period over that rate in the initial period.
The third and final step is to normalize the adjusted forecasts to the total of new World Bank lending. This step also allows the user to force changes in lending to specific countries via an exogenous multiplier ( xwblnfinm ).
The outstanding loan portfolio for each country can then be updated.
The third decision of the World Bank as agent was specified to be the target sector of loans within recipient countries. In large part because of the other representations within IFs, five such targets are specified: education, health, unskilled worker households, skilled worker households, and other uses. At this point in model development a single parameter ( xwbsectar ) has been added with default values that draw upon data gathered about past Bank practice to guide flows to uses within recipient countries. A final adjustment term is put unto that equation based upon algorithmic analysis in the first year; for instance, if it is found that supposed World Bank lending to the education sector exceeds government spending in that sector, the adjustment factor reduces it.
The fourth and final set of decisions concern the terms of the lending. Again, parameters exist to change interest rates ( xwblintr ) and repayment periods ( xwblnrep r). Currently, returns of funds to the World Bank and the IMF are assumed in the base case to be at the rate of 5% of principal each year, with 3% real interest payments, about the rate of global economic growth.
The IMF representation is fundamentally parallel to that for the World Bank. It determines in the same manner how much credit the IMF has to offer. And it determines the initial target of credits based on the scaling up of initial credits, the process that computed on a base calculation for the World Bank. There is no representation of IMF agency based on analysis around the drivers of its credit offering over time (such as liquidity problems of recipients); instead credit levels are now changed over time with GDP of recipients and an exogenous multiplier ( ximfcrfinm ). Agency could be developed analogously to the representation in the World Bank, although the real-world IMF process is more politically charged than are Bank lending decisions.
The three terms that adjust total IMF credits across years begin with repayments, the sum of flows out of recipient countries (XIMFCRFOUT) to pay either interest (at simfcrintr ) or principal (at ximfcrrepr ).
The second term specifies the flow of subscriptions by donor countries to the IMF (XIMFSUBF) and is determined by the overall growth in IMF credits ( ximfcreditr ).
The third term carries the new credits provided to recipients (XIMFCRFIN). This is an initial computation to obtain the overall level of global IMF credits. Country-specific values will be recomputed later, but normalized to this overall level.
The next step is the reallocation of flows into countries. Instead of the more sophisticated agency representation of the World Bank, credit inflows are adjusted from initial value by growth in the potential GDP and by an exogenous multiplier ( ximcrfinm ). After an initial computation, the values are then normalized across countries so that the total global flows computed above still hold.
Given the final calculation of IMF credit inflows, it is possible to compute the total IMF credit position (XIMFCREDIT) of each country (which will be negative for subscribers).
There were many data-related issues and decisions made to initialize the World Bank and IMF representations. The WDI database provides information on annual loans from the World Bank in two categories, those of the International Bank for Reconstruction and Development (IBRD) and those from the International Development Bank (IDA). The latter loans tend to have more concessional terms than do the former. Similarly, the database provides information on annual credits from the IMF, dividing them into concessional and non-concessional.
For the purposes of the SAM at this stage, the pre-processor sums the two types of loans and two types of credits into a total annual lending by the Bank and total credit flow from the IMF. Because these values tend to fluctuate substantially from year to year, and because the final years of the 1990s were a rather unusual period in global financial markets, the values set for initialization of forecasts are calculated from 5-year averages of loans and credits received as a percent of GDP in recent years, with the average rate then applied to the GDP of developing countries in the model's base year.
Unfortunately, the data only indicate net flows. For purposes of the dynamics of the model, it is important to distinguish repayment of loans or credits and interest on loans from new inflows. Net flows from the World Bank were decomposed into estimates of inflows (XWBLNFIN) and outflows (XWBLNFOUT) by estimating the value of repayments (outflows) based on the stock of loans from the Bank; initialization of stocks will be discussed below. The estimate of outflows assumed a 20-year life on loans and therefore 5% annual repayment, as well as a 3% interest rate via parameters that have now been made flexible for intervention by users. New inflows are then calculated as net flows minus the outflows. Exactly the same process was followed for IMF credits.
The pre-processor turns next to lending of the World Bank and credits from the IMF, collectively the International Financial Institutions (IFIs). It again uses WDI data for initial conditions of total loans held by borrowing countries (XWBLOANS). Nulls are filled with zeros. The same is done for IMF credits (XIMFCREDIT). In both cases, it is assumed that the bulk of funds loaned by the two IFIs come from subscriptions that ultimately constitute assets of developed countries. The pre-processor assigns assets by size of GDP.