Julien Fouquau

What Drove the Massive Hoarding of International Reserves in Emerging Economies? A Time‐varying Approach

Existing empirical models fail to explain the surge in the accumulation of foreign exchange reserves by emerging countries during the last decade. In this paper, we estimate the demand for international reserves on a panel of emerging countries using a Time-Varying Panel Smooth Transition Regression model (TV-PSTR) to relax the assumption of coefficient stability in the relationship. We find evidence that the parameters are not constant. In addition, we observe that the coefficients remained relatively stable until 2000 and then increased gradually and strongly thereafter. Our specification accounts for an acceleration that linear specifications fail to explain. Finally, we find that mercantilist motives are the major driver of this acceleration.

Energy demand models: a threshold panel specification of the ‘Kuznets curve’

This article proposes an original panel specification of the energy demand model. Based on panel threshold regression models, we derive country-specific and time-specific energy elasticity. We find a fall of the elasticity when the income level increase.

Economic Development and Energy Intensity: a Panel Data Analysis

The energy-GDP ratio, or ratio of total national primary energy consumption to GDP, is a measure of the Energy Intensity of the economy (henceforward noted as EI). It represents the energy required to generate a unit of national output. Its evolution over time shows whether the economy becomes more or less energy intensive. Projections of national energy demand under different growth scenarios depend upon the explicit or implicit value of this ratio. It can also be used to define an objective of energy policy.

The Feldstein-Horioka Puzzle : a Panel Smooth Transition Regression Approach

This paper proposes an original framework to determine the relative influence of fivefactors on the Feldstein and Horioka result of OECD countries with a strong saving-investment association. Based on panel threshold regression models, we establishcountry-specific and time-specific saving retention coefficients for 24 OECD coun-tries over the period 1960-2000. These coefficients are assumed to change smoothly,as a function of five threshold variables, considered as the most important in theliterature devoted to the Feldstein and Horioka puzzle. The results show that; de-gree of openness, country size and current account to GDP ratios have the greatestinfluence on the investment-saving relationship.

The determinants of international reserves in the emerging countries: a nonlinear approach

In this article, we adopt a nonlinear approach to examine the dynamics of the international reserves holdings by the emerging economies. To do so, we estimate the demand for international reserves with a Panel Smooth Transition Regression (PSTR) model that loosens two restricting hypotheses, homogeneity and time-stability. We find evidence for the presence of a nonlinear behaviour in the demand for international reserves, a result that is new to the literature. The coefficients are found to change smoothly, as a function of two threshold variables – out of five candidates tested in total. Our specification accounts for the acceleration of foreign exchange reserves accumulation that the linear specifications fail to explain.

Short-run electricity load forecasting with combinations of stationary wavelet transforms

Short-term forecasting of electricity load is an essential issue for the management of power systems and for energy trading. Specific modeling approaches are needed given the strong seasonality and volatility in load data. In this paper, we investigate the benefit of combining stationary wavelet transforms to produce one day-ahead forecasts of half-hourly electric load in France. First, we assess the advantage of decomposing the aggregate load into several subseries with a wavelet transform. Each component is predicted separately and aggregated to get the final forecast. One innovation of this paper is to propose several approaches to deal with the boundary problem which is particularly detrimental in electricity load forecasting. Second, we examine the benefit of combining forecasts over individual models. An extensive out-of-sample evaluation shows that a careful treatment of the border effect is required in the multiresolution analysis. Combinations including the wavelet predictions provide the most accurate forecasts. This result is valid with several assumptions about the forecast error in temperature and for different types of hours (peak, normal, off-peak), different days of the week and various forecasting periods.