Foreign inflows and economic growth: An emiprical study of the SAARC region

The study examines and highlights the impact of selected foreign inflows (aid, trade, FDI, debt and remittances) on the economic growth of the South Asian Association for Regional Cooperation (SAARC) countries. The existent literature lacks a comprehensive analysis of the SAARC countries as countries like Afghanistan, Bhutan and the Maldives have largely been ignored due to the shorter time periods of available data. The study is empirical in nature and utilizes panel data techniques on macroeconomic data for the period 2008–2015. Foreign aid and foreign direct investment are found to impact economic growth positively. Foreign debt and trade flows are found to adversely affect economic growth. No relationship is established between the flow of remittances and the economic growth of these countries. The obtained results are robust to different proxy variables and the addition of macroeconomic variables. For the first time, the study provides policy implications based on the data of all SAARC countries. The study recommends focusing on increasing the inflows of resources in the form of aid and foreign direct investment (FDI) from the developed world to achieve higher economic growth.     

How capital markets assess the credibility and accuracy of CSR reporting: Exploring the effects of assurance quality and CSR restatement issuance

This research examines how the credibility and accuracy of corporate social responsibility (CSR) disclosures enhance market confidence by exploring their effect on the cost of capital. How do capital markets react to higher-quality assurance of CSR reporting? Can the hypothetical reduction in the cost of capital that assurance quality produces be explained by restatements of previous information given in these CSR reports? We explore the relationship between assurance quality, as a proxy for credibility and market confidence, and the mediating effect of CSR restatements as indicators of accuracy. We propose regression models with a sample of CSR reports issued by European companies. Building upon the signalling and legitimacy theories, the results support the positive effect of higher assurance quality statements on market confidence by confirming a decrease in the cost of capital; assurance quality gives an indication of credibility to the capital market and restatements related to methodological updates signal accuracy. The reduction in the cost of capital brought on by higher assurance quality appears to be determined by the issuance of CSR restatements, which create legitimacy for both client companies and assurance providers. CSR reporting and assurance have reached a greater level of maturity as demonstrated by the evolution of these practices and financial market perceptions.     

Estimation methods for stochastic volatility models: a survey

Abstract.  Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index.     

Regression Modeling for the Valuation of Large Variable Annuity Portfolios

Variable annuities are insurance products that contain complex guarantees. To manage the financial risks associated with these guarantees, insurance companies rely heavily on Monte Carlo simulation. However, using Monte Carlo simulation to calculate the fair market values of these guarantees for a large portfolio of variable annuities is extremely time consuming. In this article, we propose the class of GB2 distributions to model the fair market values of guarantees to capture the positive skewness typically observed empirically. Numerical results are used to demonstrate and evaluate the performance of the proposed model in terms of accuracy and speed.     

Evolutions and Contradictions in Mainstream Macroeconomics: The Case of Olivier Blanchard

This article traces the complex intellectual path of Olivier Blanchard, a personification of the controversial evolution of macroeconomic research over the last three decades. After contributing to consolidation of the core of mainstream macroeconomics, Blanchard recently suggested ‘rethinking’ some of its key aspects to take stock of the lessons of the 2008 Great Recession, which he witnessed as the International Monetary Fund’s Chief Economist. This welcome discussion, which according to Blanchard should open mainstream macroeconomics to heterodox thinking, has so far produced a certainly interesting albeit theoretically contradictory synthesis and limited policy consequences. The most paradigmatic aspect of this rethinking of macroeconomics is represented by the abandonment in teaching of aggregate supply and demand in favor of a revival of the IS–LM model complemented by the Phillips curve. While this change of perspective does allow for the instability of ‘natural’ equilibrium to be emphasized, a deeper reading may prove incompatible with the neoclassical foundations of the mainstream approach.     

Are EU trade preferences really effective? An impact evaluation assessment of the Southern Mediterranean Countries’ case

This work assesses the causal impact of the EU trade preferences granted to the Southern Mediterranean Countries (SMCs) in agriculture and fishery products over the period 2004–2014. It overcomes some of the weaknesses of previous assessments and presents several methodological improvements. Firstly, it relies on a continuous treatment – i.e. preferential margins – to capture the ‘average treatment effect’ of trade preferences, rather than on a binary treatment based on dummy variables. Secondly, it uses highly disaggregated data at sectoral level in order to evaluate properly the preferential treatment. Thirdly, it applies a non-parametric matching technique for continuous treatment – specifically, a generalized propensity score matching. The results show, on the one hand, that the impact of the EU preferences is positive and significant on SMCs trade and is better evaluated using impact evaluation techniques. On the other hand, they demonstrate that the relationship between preferences and trade flows is asymmetric and warn against the risk of providing too much of a good thing. These results raise important issues for policy-making. First, they demonstrate that raising the level of preferences is not the solution to foster the SMCs trade towards EU. Second, that the policy-makers should put more emphasis on complementary factors other than trade barriers.     

The Adjusted Big Mac Methodology: A Clarification

The Economist's adjusted Big Mac index takes GDP into account in currency valuation, but the methodology is not explained. We show that the key to understanding the methodology is to distinguish between a currency's bilateral valuation (versus a specific currency) and the currency's overall valuation (versus a “basket” of a large number of currencies). Also, the adjusted Big Mac estimates of intrinsic foreign exchange (FX) rates have been better forecasts of actual FX changes than those of the original “raw” Big Mac index.     

Prediction regions for interval-valued time series

We approximate probabilistic forecasts for interval-valued time series by offering alternative approaches. After fitting a possibly non-Gaussian bivariate vector autoregression (VAR) model to the center/log-range system, we transform prediction regions (analytical and bootstrap) for this system into regions for center/range and upper/lower bounds systems. Monte Carlo simulations show that bootstrap methods are preferred according to several new metrics. For daily S&P 500 low/high returns, we build joint conditional prediction regions of the return level and volatility. We illustrate the usefulness of obtaining bootstrap forecasts regions for low/high returns by developing a trading strategy and showing its profitability when compared to using point forecasts.