China and the changing landscape of the world economy

The rapid development of emerging markets is changing the landscape of the world economy and may have profound implications for international relations. China is often regarded as the most influential emerging market economy because, during the last three decades, it has become increasingly integrated into the world economic system and its success and failure now affect the well-being of other nations in the world. As the financial crisis in the US and EU intensifies, the economic prosperity of the world depends to a large extent on the sustained development of the Chinese economy and other emerging markets, and vice versa.

Why do people non-demand reveal in hypothetical double referenda for public goods?

Hypothetical contingent valuation surveys used to elicit values for environmental and other public goods often employ variants of the referendum mechanism due to the cognitive simplicity and familiarity of respondents with this voting format. One variant, the double referendum mechanism, requires respondents to state twice how they would vote for a given policy proposal given their cost of the good. Data from these surveys often exhibit anomalies inconsistent with standard economic models of consumer preferences. There are a number of published explanations for these anomalies, mostly focusing on problems with the second vote. This article investigates which aspects of the hypothetical task affect the degree of nondemand revelation and takes an individual-based approach to identifying people most likely to non-demand reveal. A clear profile emerges from our model of a person who faces a negative surplus i.e. a net loss in the second vote and invokes non self-interested, non financial motivations during the decision process.

Necessary conditions for demand revelation in double referenda

This paper demonstrates a set of necessary conditions that should generate unbiased, internally consistent estimates of willingness to pay (WTP) from a double referendum mechanism. These conditions are also sufficient for demand revelation in an experimental laboratory environment. However, the control over the mechanism achieved in the lab may not be transferrable to the field and WTP estimates derived from field surveys may remain biased. (c) 2008 Elsevier Inc. All rights reserved.

Learning design contingent valuation (LDCV): NOAA guidelines, preference learning and coherent arbitrariness

We extend the contingent valuation (CV) method to test three differing conceptions of individuals' preferences as either (i) a-priori well-formed or readily divined and revealed through a single dichotomous choice question (as per the NOAA CV guidelines [K. Arrow, R. Solow, P.R. Portney, E.E. Learner, R. Radner, H. Schuman, Report of the NOAA panel on contingent valuation, Fed. Reg. 58 (1993) 4601-4614]); (ii) learned or 'discovered' through a process of repetition and experience [J.A. List, Does market experience eliminate market anomalies? Q. J. Econ. (2003) 41-72; C.R. Plott, Rational individual behaviour in markets and social choice processes: the discovered preference hypothesis, in: K. Arrow, E. Colombatto, M. Perleman, C. Schmidt (Eds.), Rational Foundations of Economic Behaviour, Macmillan, London, St. Martin's, New York, 1996, pp. 225-250]; (iii) internally coherent but strongly influenced by some initial arbitrary anchor [D. Ariely, G. Loewenstein, D. Prelec, 'Coherent arbitrariness': stable demand curves without stable preferences, Q. J. Econ. 118(l) (2003) 73-105]. Findings reject both the first and last of these conceptions in favour of a model in which preferences converge towards standard expectations through a process of repetition and learning. In doing so, we show that such a 'learning design CV method overturns the 'stylised facts' of bias and anchoring within the double bound dichotomous choice elicitation format. (C) 2007 Elsevier Inc. All rights reserved.

Resolving questions about bias in real and hypothetical referenda

Despite 10 years of research on behavior in hypothetical referenda, conflict remains in the literature on whether or not the mechanism generates biased responses compared to real referenda, and the nature and source of any such bias. Almost all previous inquiry in respect of this issue has concentrated on bias at the aggregate level. This paper reports a series of three experiments which focuses on bias at the individual level and how this can translate to bias at the aggregate level. The authors argue that only an individual approach to hypothetical bias is consistent with the concept of incentive compatibility. The results of these experiments reflect these previous conflicting findings but go on to show that individual hypothetical bias is a robust result driven by the differing influence of pure self-interest and other-regarding preferences in real and hypothetical situations, rather than by a single behavioral theory such as free riding. In a hypothetical situation these preferences cause yea-saying and non-demand revealing voting. This suggests that investigation of individual respondents in other hypothetical one-shot binary choices may also provide us with insights into aggregate behavior in these situations.

Neural network forecasts of input-output technology

A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.

Parametric and non-parametric estimates of willingness to pay for forest recreation in Northern Ireland: A discrete choice contingent valuation study with follow-ups

In this study we show that forest areas contribute significantly to the estimated benefits from om outdoor recreation in Northern Ireland. Secondly we provide empirical evidence of the gains in the statistical efficiency of both benefit and parameter estimates obtained by analysing follow-up responses with Double Bounded interval data analysis. As these gains are considerable, it is clearly worth considering this method in CVM survey design even when moderately large sample sizes are used. Finally we demonstrate that estimates of means and medians of WTP distributions for access to forest recreation show plausible magnitude, are consistent with previous UK studies, and converge across parametric and non-parametic methods of estimation.

A note on the warm glow of giving and scope sensitivity in contingent valuation studies

This note develops a behavioral framework to classify individual contingent valuation (CV) respondents in terms of the warm glow and altruistic motives in their WTP responses. We suggest that at least five possible behavioral categories for CV responses may exist, depending on the type of underlying preferences and whether respondents are satiated or non-satiated with respect to the good. An empirical example suggests that the warm glow motive may be present in the majority of bids, although its presence does not necessarily preclude scope sensitivity to the quantity/quality of an environmental good. (C) 2000 Elsevier Science B.V. All rights reserved.

Valuing the recreational benefits from the creation of nature reserves in Irish forests

Data from a large-scale contingent valuation study are used to investigate the effects of forest attributes on willingness to pay for forest recreation in Ireland. In particular, the presence of a nature reserve in the forest is found to significantly increase the visitors' willingness to pay. A random utility model is used to estimate the welfare change associated with the creation of nature reserves in all the Irish forests currently without one. The yearly impact on visitors' economic welfare of new nature reserves approaches half a million pounds per annum, exclusive of non-recreational values. (C) 2000 Elsevier Science B.V. All rights reserved.

TESTING FOR STATIONARITY IN HETEROGENEOUS PANEL DATA IN THE CASE OF MODEL MISSPECIFICATION

This paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N -> infinity simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro-panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over-rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (

ARE OECD MACROECONOMIC VARIABLES TREND STATIONARY? EVIDENCE FROM PANEL STATIONARITY TESTS ALLOWING FOR A STRUCTURAL BREAK AND CROSS-SECTIONAL DEPENDENCE

This article applies the panel stationarity test with a break proposed by Hadri and Rao (2008) to examine whether 14 macroeconomic variables of OECD countries can be best represented as random walk or stationary fluctuations around a deterministic trend. In contrast to previous studies, based essentially on visual inspection of the break type or just applying the most general break model, we use a model selection procedure based on BIC. We do this for each time series so that heterogeneous break models are allowed for in the panel. Our results suggest, overwhelmingly, that if we account for a structural break, cross-sectional dependence and choose the break models to be congruent with the data, then the null of stationarity cannot be rejected for all the 14 macroeconomic variables examined in this article. This is in sharp contrast with the results obtained by Hurlin (2004), using the same data but a different methodology.