Does foreign aid really raise per capita income? A time series perspective

Abstract. We analyze the relationship between per capita income and foreign aid. We employ annual data and five‐year averages and carefully examine the time‐series properties of the data. Panel estimations with dynamic feasible generalized least‐squares (DFGLS) show that aid generally has an insignificant or minute negative significant impact on per capita income (particularly in highly aid‐dependent countries). This holds true for countries with different levels of human development and income, as well as for different regions. We also find that aid has a small positive impact on investment, but a significant negative impact on domestic savings (crowding out) and the real exchange rate (appreciation). JEL classification: F35, O11, C23, C51     

Estimation of zero-intelligence models by L1 data

A unit volume zero-intelligence (ZI) model is defined and the distribution of its L1 process is recursively described. Further, a generalized ZI model allowing non-unit market orders, shifts of quotes and general in-spread events is proposed and a formula for the conditional distribution of its quotes is given, together with a formula for price impact. For both the models, MLE estimators are formulated and shown to be consistent and asymptotically normal. Consequently, the estimators are applied to data of six US stocks from nine electronic markets. It is found that more complex variants of the models, despite being significant, do not give considerably better predictions than their simple versions with constant intensities.     

Pseudo empirical likelihood method in the presence of missing data

In this paper, we propose an estimator for the population mean when some observations on the study and auxiliary variables are missing from the sample. The proposed estimator is valid for any unequal probability sampling design, and is based upon the pseudo empirical likelihood method. The proposed estimator is compared with other estimators in a simulation study.     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.     

Are firms accessing venture funding more financially constrained? New evidence from capital structure adjustments

We analyze whether firms that receive venture capital (VC) at a later date face more financial constraints than a one-by-one matched sample of firms that did not receive VC funding (control group). The aim is to check whether their financial flexibility explains why they decide to seek external equity funding. In contrast with other papers, which focus on the sensitivity of investments to cash flow, we study this issue by applying a dynamic model to analyze the speed of adjustment to their target debt levels prior to receiving the first VC investment. We analyze a representative sample of 237 Spanish unlisted firms that received VC between 1995 and 2007 and its corresponding control group. We find that firms that receive VC funding show a significantly lower speed of adjustment than their matched peers before the initial VC round. It seems that the former are more concerned about funding the required investments than about adjusting the firm's debt ratio to a target level. Our results confirm the role of VC in filling the equity gap in constrained unlisted firms. From a capital structure perspective, VC may become a tool for these companies to balance their capital structure in a growth process.     

Visual displays: analytical study and applications to graphs and real data

Principal axis methods such as principal component analysis (PCA) and correspondence analysis (CA) are useful for identifying structures in data through interesting planar graphic displays. However, some kinds of data sets can be dealt alternatively with PCA or CA. This paper focuses on methods, such as PCA and CA, and on visual displays. Our aim is to illustrate the implications for a potential user of selecting either method, and its advantages and disadvantages, from an applied point of view. This is a matter covered broadly in textbooks and elsewhere considering theoretical arguments. Our purpose is to contribute to the comparison between these methods, over the same data set, in order to illustrate them for the practitioner. In the first part of this paper we present a novel analytical study of a binary matrix associated with a non-oriented axis-symmetric graph and show that CA outperforms standardized PCA for the reconstitution and visualization of such kind of graphs. In the second part we present a case using real data dealing with the distribution of employees in different economic sectors for the countries of the European Union, analyzed by means of standardized PCA and two-way CA, in order to see the differences between the two methods in practice.     

Altruism and the Economic Values of Environmental and Social Policies

Altruism is a type of non-use value which can have different definitions depending on the type of goods entering the utility function of the altruists and their expectations about the contributions of others. The purpose of this paper is to measure the trade-offs between different types of altruist values originating from social and environmental policies. Environmental policies are concerned with reducing health effects from a power plant while social policies involve both the attainment of public facilities for education and leisure and an increase in the income of the affected population. The empirical application utilizes a choice experiment technique which allows for valuation of multiple goods. Health effects are decomposed into the values of the risk of becoming ill, the duration of the episodes and the limitations imposed by illness. Altruist values are elicited from a population that is not affected by pollution. Results show that altruism is significant for policies directed to reducing health effects and improving the income level of the affected population, whereas there is egoism for a policy aimed at improving public facilities in the polluted suburb. The value of altruism is significantly influenced by the expectations of net benefits to be received by the affected population.     

A note on how to measure hubbing practices in airline networks

Benefits and costs associated to hubbing practices of airlines are still subject to much debate. In the previous literature, some standard spatial concentration indices have been proposed to measure it. However, we show that these indices are “ill-defined” because they do not take into account the salient characteristic of hubbing: connecting passengers. The purpose of this research is to present a new methodology which avoids the pitfalls of other methods. Our new methodology also analyzes the level of concentration of the connecting passengers studying two different dimensions: hub airports and routes. Finally, we apply our methodology to some US carriers.