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Ample natural resource revenues create both opportunities and challenges for a sovereign to transform its natural resources into well-managed financial assets. Hence, inter-temporal smoothing of revenue and consumption/investment moves to the center stage of macroeconomic policies. The questions arising from natural resource wealth accumulation are becoming more pressing for many countries, given the need to achieve intergenerational equity in a context where commodity prices may not continue their upward trajectory of the past decade. Addressing these questions requires a flexible sovereign asset-liability management (SALM) framework that integrates various macroeconomic and financial trade-offs with the aim of containing financial risk to the sovereign balance sheet. The framework and policy advice aims to guide policymakers across different institutions in weighing those trade-offs.

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The IMF Executive Board endorsed in October 2014 the inclusion of key features of enhanced pari passu provisions and collective action clauses (CACs) in new international sovereign bonds.1 Specifically, the Executive Board endorsed the use of (i) a modified pari passu provision that explicitly excludes the obligation to effect ratable payments, and (ii) an enhanced CAC with a menu of voting procedures, including a "single-limb" aggregated voting procedure that enables bonds to be restructured on the basis of a single vote across all affected instruments, a two-limb aggregated voting procedure, and a series-by-series voting procedure.2 Directors supported an active role for the IMF in promoting the inclusion of these clauses in international sovereign bonds.3 The IMFC and the G20 further called on the IMF to promote the use of such clauses and report on their inclusion.Since that time, the IMF has published periodic progress reports on inclusion of the enhanced clauses.4 These reports found that since the Executive Board's endorsement, substantial progress had been made in incorporating the enhanced clauses, with approximately 85 percent of new international sovereign bond issuances since October 2014 (in nominal principal amount) including such clauses. The reports also found that there was no observable market impact on inclusion of the enhanced clauses. However, the reports noted that the outstanding stock without the enhanced clauses remained significant, with issuers showing little appetite for liability management exercises to accelerate the turnover.This paper provides a further update on the inclusion of the enhanced clauses and on the outstanding stock of international sovereign bonds as of September 30, 2017. Section II reports on the inclusion of these enhanced provisions, finding that the vast majority of issuers are including these clauses, with only a few countries standing out against the market trend. Section II also provides an update on the outstanding stock, indicating that while the percentage of the outstanding stock with the enhanced clauses is increasing, a significant percentage of the stock still does not and little action has been taken by issuers to increase the rate of turnover. Section III briefly reports on the use of different bond structures, and Section IV describes the staff's ongoing outreach efforts and next steps.

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This paper proposes a method of testing whether a time series is a martingale. The procedure develops an asymptotic theory for the shape of the spectral distribution function of the first differences. Under the null hypothesis, this shape should be a diagonal line. several tests are developed which determine whether the deviation of the sample spectral distribution function from a diagonal line, when treated as an element of a function space, is too erratic to be attributable to sampling error. These tests are consistent against all moving average alternatives. The testing procedure possesses the additional advantage that it eliminates discretion in choosing a particular H[sub 1] by the researcher and therefore guards against data mining, The tests may further be adjusted to analyze subsets of frequencies in isolation, which can enhance power against particular alternatives. Application of the test to stock prices finds some evidence against the random walk theory.

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It is widely acknowledged that many financial markets exhibit a considerably greater degree of kurtosis (and sometimes also skewness) than is consistent with the Geometric Brownian Motion model of Black and Scholes (1973). Among the many alternative models that have been proposed in this context, two have become especially popular in recent years: models of jump-diffusions, and models of stochastic volatility. This paper explores the statistical properties of these models with a view to identifying simple criteria for judging the consistency of either model with data from a given market; our specific focus is on the patterns of skewness and kurtosis that arise in each case as the length of the interval of observations changes. We find that, regardless of the precise parameterization employed, these patterns are strikingly similar within each class of models, enabling a simple consistency test along the desired lines. As an added bonus, we find that for most parameterizations, the set of possible patterns differs sharply across the two models, so that data from a given market will typically not be consistent with both models. However, there exist exceptional parameter configurations under which skewness and kurtosis in the two models exhibit remarkably similar behavior from a qualitative standpoint. The results herein will be useful to empiricists, theorists and practitioners looking for parsimonious models of asset prices.

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This paper examines the sources of expenditure growth in heart attack treatment. We first show that essentially all of cost growth is a result of the diffusion of particular intensive technologies; the prices paid for a given level of technology have been constant or falling over time. We then examine the reasons for this technology diffusion. We distinguish six factors that may influence technology diffusion: organizational factors within hospitals; the insurance environment in which technology is reimbursed; public policy regulating new technology; malpractice concerns; competitive or cooperative interactions among providers; and demographic composition. We conclude that insurance variables, technology regulation, and provider interactions have the largest quantitative effect on technological diffusion. These factors affect both technology acquisition and the frequency of technology use.

Assets (Accounting)