Predicting migratory flight altitudes by physiological migration models

Using the altitudinal profiles of wind, temperature, pressure, and humidity in three flight models, we tried to explain the altitudinal distributions of nocturnal migrants recorded by radar above a desert in southern Israel. In the simplest model, only the tailwind component was used as a predictor of the most preferred flight altitude (T model). The energy model (E model) predicted flight ranges according to mechanical power consumption in flapping flight depending on air density and wind conditions, assuming optimal adjustment of airspeed and compensation of crosswinds, and including the influence of mass loss during flight. The energy-water model (EW model) used the same assumptions and parameters as the E model but also included restrictions caused by dehydration. Because wind was by far the most important factor governing altitudinal distribution of nocturnal migrants, differences in predictions of the three models were small. In a first approach, the EW model performed slightly better than the E model, and both performed slightly better than the T model. Differences were most pronounced in spring, when migrants should fly high according to wind conditions, but when climbing and descending they must cross lower altitudes where conditions are better with respect to dehydration. A simplified energy model (Es model) that omits the effect of air density on flight costs explained the same amount of variance in flight altitude as the more complicated E and EW models. By omitting the effect of air density, the Es model predicted lower flight altitudes and thus compensated for factors that generally bias height distributions downward but are not considered in the models (i.e. climb and descent through lower air layers, cost of ascent, and decrease of oxygen partial pressure with altitude). Our results confirm that wind profiles, and thus energy rather than water limitations, govern the altitudinal distribution of nocturnal migrants, even under the extreme humidity and temperature conditions in the trade wind zone.

Energy expenditure in relation to flight speed: what is the power of mass loss rate estimates?

The relationship between mass loss rate and chemical power in flying birds is analysed with regard to water and heat balance. Two models are presented: the first model is applicable to situations where heat loads are moderate. i.e. when heat balance can be achieved by regulating non-evaporative heat loss, and evaporative water loss is minimised. The second model is applicable when heat loads are high, non-evaporative heat loss is maximised. and heat balance has to be achieved by regulating evaporative heat loss. The rates of mass loss of two Thrush Nightingales Luscinia luscinia and one Teal Anas crecca were measured at various flight speeds in a wind tunnel. Estimates of metabolic water production indicate that the Thrush Nightingales did not dehydrate during experimental flights. Probably, the Thrush Nightingales maintained heat balance without actively increasing evaporative cooling. The Teal, however, most likely had to resort to evaporative cooling, although it may not have dehydrated. Chemical power was estimated from our mass loss rate data using the minimum evaporation model for the Thrush Nightingales and the evaporative heat regulation model for the Teal. For both Thrush Nightingales and the Teal, the chemical power calculated from our mass loss rate data showed a greater change with speed (more 'U-shaped' curve) than the theoretically predicted chemical power curves based on aerodynamic theory. The minimum power speeds calculated from our data differed little from theoretical predictions but maximum range speeds were drastically different. Mass loss rate could potentially be used to estimate chemical power in flying birds under laboratory conditions where temperature and humidity are controlled. However, the assumptions made in the models and the model predictions need further testing.

A sequential purchasing power parity test for panels of large cross-sections and implications for investors

In this paper we use monthly time series data for not less than 64 countries and a new sequential approach to test for purchasing power parity (PPP). The results are strong in that the evidence in favor of PPP is very weak. In fact, for the US-dollar-based exchange rates the evidence is basically non-existent. In order to eliminate the effect of the base currency, we also apply the sequential PPP test to all pairs of exchange rates, and find similarly weak evidence of PPP. However, for those rates where evidence is found, using a technical trading rule, we find evidence of significant profits. The predictability of the stationary pairs is therefore important for investors.

New tools for understanding the local asymptotic power of panel unit root tests

Abstract Motivated by the previously documented discrepancy between actual and predicted power, the present paper provides new tools for analyzing the local asymptotic power of panel unit root tests. These tools are appropriate in general when considering panel data with a dominant autoregressive root of the form ^ρi=1+^ciN-^κT-^τ, where i=1,...,N indexes the cross-sectional units, T is the number of time periods and ^ci is a random local-to-unity parameter. A limit theory for the sample moments of such panel data is developed and is shown to involve infinite-order series expansions in the moments of ^ci, in which existing theories can be seen as mere first-order approximations. The new theory is applied to study the asymptotic local power functions of some known test statistics for a unit root. These functions can be expressed in terms of the expansions in the moments of ^ci, and include existing local power functions as special cases. Monte Carlo evidence is provided to suggest that the new results go a long way toward bridging the gap between actual and predicted power.

New improved tests for cointegration with structural breaks

This article proposes Lagrange multiplier-based tests for the null hypothesis of no cointegration. The tests are general enough to allow for heteroskedastic and serially correlated errors, deterministic trends, and a structural break of unknown timing in both the intercept and slope. The limiting distributions of the test statistics are derived, and are found to be invariant not only with respect to the trend and structural break, but also with respect to the regressors. A small Monte Carlo study is also conducted to investigate the small-sample properties of the tests. The results reveal that the tests have small size distortions and good power relative to other tests. © 2007 The Authors Journal compilation 2007 Blackwell Publishing Ltd.

Is there really a unit root in the inflation rate? More evidence from panel data models

Time series unit root evidence suggests that inflation is nonstationary. By contrast, when using more powerful panel unit root tests, Culver and Papell (1997) find that inflation is stationary. In this article, we test the robustness of this result by applying a battery of recent panel unit root tests. The results suggest that the stationarity of inflation holds even after controlling for cross-sectional dependence and structural change.

Mixed signals among tests for panel cointegration

In this paper, we study the effect that different serial correlation adjustment methods can have on panel cointegration testing. As an example, we consider the very popular tests developed by Pedroni [Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics 61, 653670., Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory 20, 597-625.]. Results based on both simulated and real data suggest that different adjustment methods can lead to significant variations in test outcome, and thus also in the conclusions. © 2007 Elsevier B.V. All rights reserved.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

A comparative study on procedure and state of the art of conventional maximum power point tracking techniques for photovoltaic system

Due to the increasing world energy demand, renewable energy systems have been significantly applied in the power generation sector. Among the renewable energy options, photovoltaic system is one of the most popular resources which has been experiencing a huge attention during recent decades. The remarkable advantages, such as static and movement free characteristics, low maintenance costs, and longevity are the primary factors for the popularity of solar generation in the late years. Nevertheless, the low PV conversion efficiency in one side and high PV material cost in the other side have made PV generation comparably expensive system. Consequently, a capable maximum power point tracking (MPPT) is all important to elicit the maximum energy from the production of PV systems. Different researches have been conducted to design a fast, simple and robust MPPT technique under uniform conditions. However, due to the series and parallel connection of PV modules and according to the use of bypass diodes, in the structure of PV modules, a conventional techniques are unable to track a true MPP. Recently, several studies have been undertaken to modify these conventional methods and enable them to track the global MPP under rapidly changing environments and partial shading (PS) conditions. This report concentrates on the state of the art of these methods and their evolution to apply under PS conditions. The recent developments and modifications are analyzed through a comparison based on design complexity, cost, speed and the ability to track the MPP under rapid environmental variations and PS conditions.

Time-series properties and empirical evidence of growth and infraestructure: revised version

After more than forty years studying growth, there are two classes of growth models that have emerged: exogenous and endogenous growth models. Since both try to mimic the same set of long-run stylized facts, they are observationally equivalent in some respects. Our goals in this paper are twofold First, we discuss the time-series properties of growth models in a way that is useful for assessing their fit to the data. Second, we investigate whether these two models successfully conforms to U.S. post-war data. We use cointegration techniques to estimate and test long-run capital elasticities, exogeneity tests to investigate the exogeneity status of TFP, and Granger-causality tests to examine temporal precedence of TFP with respect to infrastructure expenditures. The empirical evidence is robust in confirming the existence of a unity long-run capital elasticity. The analysis of TFP reveals that it is not weakly exogenous in the exogenous growth model Granger-causality test results show unequivocally that there is no evidence that TFP for both models precede infrastructure expenditures not being preceded by it. On the contrary, we find some evidence that infras- tructure investment precedes TFP. Our estimated impact of infrastructure on TFP lay rougbly in the interval (0.19, 0.27).

Nonparametric specification tests for conditional duration models

This paper deals with the testing of autoregressive conditional duration (ACD) models by gauging the distance between the parametric density and hazard rate functions implied by the duration process and their non-parametric estimates. We derive the asymptotic justification using the functional delta method for fixed and gamma kernels, and then investigate the finite-sample properties through Monte Carlo simulations. Although our tests display some size distortion, bootstrapping suffices to correct the size without compromising their excellent power. We show the practical usefulness of such testing procedures for the estimation of intraday volatility patterns.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE transactions data, with special attention to IBM price durations. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

Purchasing power parity: the choice of price index

Looking closely at the PPP argument, it states that the currencies purchasing power should not change when comparing the same basket goods across countries, and these goods should all be tradable. Hence, if PPP is valid at all, it should be captured by the relative price indices that best Öts these two features. We ran a horse race among six di§erent price indices available from the IMF database to see which one would yield higher PPP evidence, and, therefore, better Öt the two features. We used RER proxies measured as the ratio of export unit values, wholesale prices, value added deáators, unit labor costs, normalized unit labor costs and consumer prices, for a sample of 16 industrial countries, with quarterly data from 1975 to 2002. PPP was tested using both the ADF and the DFGLS unit root test of the RER series. The RER measured as WPI ratios was the one for which PPP evidence was found for the larger number of countries: six out of sixteen when we use DF-GLS test with demeaned series. The worst measure of all was the RER based on the ratio of foreign CPIs and domestic WPI. No evidence of PPP at all was found for this measure.

Growth, increasing returns, and public infrastructure : time series evidence

Initial endogenous growth models emphasized the importance of external effects and increasing retums in explaining growth. Empirically, this hypothesis can be confumed if the coefficient of physical capital per hour is unity in the aggregate production function. Previous estimates using time series data rejected this hypothesis, although cross-country estimates did nol The problem lies with the techniques employed, which are unable to capture low-frequency movements of high-frequency data. Using cointegration, new time series evidence confum the theory and conform to cross-country evidence. The implied Solow residual, which takes into account externaI effects to aggregate capital, has its behavior analyzed. The hypothesis that it is explained by government expenditures on infrasttucture is confIrmed. This suggests a supply-side role for government affecting productivity.

Do shocks permanently change output? : Local persistency in economic time series

While it is recognized that output fuctuations are highly persistent over certain range, less persistent results are also found around very long horizons (Conchrane, 1988), indicating the existence of local or temporary persistency. In this paper, we study time series with local persistency. A test for stationarity against locally persistent alternative is proposed. Asymptotic distributions of the test statistic are provided under both the null and the alternative hypothesis of local persistency. Monte Carlo experiment is conducted to study the power and size of the test. An empirical application reveals that many US real economic variables may exhibit local persistency.