Oil prices and the real exchange rate in Iran: an ARDL bounds testing approach

This article examines the impact of oil prices on the real exchange rate in Iran during the 1961–2014 period using the autoregressive distributed lag approach to cointegration as the estimation method. We find that higher oil prices lead to appreciation of the real exchange rate. The results reveal that oil prices have both short-run and long-run effects on the real exchange rate.     

Four steps to exporting success

True, selling to Malaysia can be as easy as selling to Arizona—provided you have your export plan in place. Planning is important for any business interested in overseas markets, but essential for the new-to-export company if it is to have a smooth and orderly entry into world markets.     

Financial flows to mexico: implications for foreign investors

The 1994–1995 Mexican peso crisis occurred with the presence there of a “new” financial force, namely nonbank private funds. Mexico's economic reforms have in recent years led to massive amounts of highly liquid (and volatile) foreign capital inflows. As the country further embraces market-based principles, long- and short-term capital will flow at an even larger scale across its border, subjecting providers as well as recipients to greater risks. This paper examines the trends in both the “traditional” as well as the “new” forms of capital inflows for the period 1981–1996. Our analysis should help the two sides of this issue: foreign investors to be better prepared in managing future economic challenges, and emerging economies—including several in Southeast Asia that suffered Mexican-style exchange-rate crises in 1997—to implement more appropriate policies, especially as they pertain to currency stability.     

The changing role of U.S.-based MNCs: A financial perspective

An increasing number of US.-based multinational companies have adopted a strategy of “inward-oriented” diversification in the 1980s. This article focuses on the ensuing financial performance of these firms, especially as compared to that of a group of U.S.-based domestic corporations. Specifically, well-known performance and risk measures are applied to a sample of multinational and domestic firms based in the U.S. The data are analyzed over three five-year periods (1979-1983, 1980-1984, and 1981-1985). The overall results, while providing total support for a few of the major issues and lending partial support to the others, seem to indicate that U.S. multinationals may have adopted a successful strategy in response to a changing global economic environment.     

Suckers in the morning,skeptics in the evening: Time-of-Day effects on consumers’ vigilance against manipulation

Persuasion knowledge is defined as a consumer’s vigilance against manipulative persuasion. In this paper, we explore the relationship between persuasion knowledge and consumer’s diurnal preference. It is proposed that evening-type consumers display enhanced persuasion knowledge relative to morning types. Also, heightened persuasion knowledge is exhibited during their respective optimal times of day for both morning-type and evening-type consumers. We propose cognitive resource availability as the key underlying mechanism for this relationship. Finally, we also demonstrate an analogous relationship between consumer skepticism and diurnal preferences. Over three studies we find supportive evidence for our claims.     

Size and Implication of Informal Economy in African Countries: Evidence from a Structural Model

This paper presents estimates of the informal economy in 41 African countries, including North Africa, Southern Africa, East Africa, Central Africa and West Africa during the period 2007–2013. Using a structural equation model with latent variables, the empirical results indicate that the average size of the informal economy in Africa (in% of formal gross domestic product) in 41 countries is 42.9%, 39.9% in 5 countries in North Africa, 40.02% in 11 countries in southern Africa, 43.24% in 6 countries of East Africa, 45.5% in 7 countries of Central Africa and 45.21% in 12 countries in West Africa. We suggest economic policy recommendations to solve the dilemma of the informal economy not only in the regions but also in different countries such as: identifying the causes of informality, the barriers to formalization and how to eliminate them; developing policies, procedures and institutions that can help informal activities meet market economy requirements, reforming legal systems and ensuring equal access for all; and finally, establishing affordable social benefits for workers.     

Are free trade agreements good for the environment? A panel data analysis

This study empirically examines the relationship between free trade agreements (FTAs) and greenhouse gas (GHG) emissions. For this purpose, we use three different FTAs: the Southern Common Market, the North American Free Trade Agreement, and the Australia–United States Free Trade Agreement. These FTAs are between developing, both developing and developed, and only developed countries, respectively. Panel unit root, panel cointegration, and fully modified ordinary least squares estimations are employed to examine the long‐run relationship between GHG emissions and trade liberalization. The results indicate that the environmental effects of FTAs depend on the different agreement types. When FTAs are between only developed or developing countries, overall there is no environmental damage, and these types of FTAs can be beneficial for the environmental quality in the long run. However, when developing and developed countries are in a trade agreement, overall environmental quality decreases due to increased GHG emissions.     

Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models

We present a neural network-based calibration method that performs the calibration task within a few milliseconds for the full implied volatility surface. The framework is consistently applicable throughout a range of volatility models—including second-generation stochastic volatility models and the rough volatility family—and a range of derivative contracts. Neural networks in this work are used in an off-line approximation of complex pricing functions, which are difficult to represent or time-consuming to evaluate by other means. The form in which information from available data is extracted and used influences network performance: The grid-based algorithm used for calibration is inspired by representing the implied volatility and option prices as a collection of pixels. We highlight how this perspective opens new horizons for quantitative modelling. The calibration bottleneck posed by a slow pricing of derivative contracts is lifted, and stochastic volatility models (classical and rough) can be handled in great generality as the framework also allows taking the forward variance curve as an input. We demonstrate the calibration performance both on simulated and historical data, on different derivative contracts and on a number of example models of increasing complexity, and also showcase some of the potentials of this approach towards model recognition. The algorithm and examples are provided in the Github repository GitHub: NN-StochVol-Calibrations.     

The object allocation problem with favoring upper ranks

We introduce (strict) favoring upper ranks, which is an extension of favoring higher ranks for random assignments. We demonstrate that ex post favoring ranks implies (strict) favoring upper ranks, and envy-freeness implies favoring upper ranks. Moreover, for at least four agents, no mechanism satisfies strict favoring upper ranks and either equal division lower bound or equal treatment of equals and lower invariance. Finally, we proved that the (modified) eating algorithm provides a random assignment that is (strict) favoring upper ranks.