Fiscal policy and asset price volatility

This paper investigates the relationship between volatility of different asset prices and the volatility of various indicators of fiscal policy (primary balance, spending and revenue). We find evidence that asset price volatility affects the volatility of fiscal policy stance in a positive and significant way. The effect comes primarily through residential property and equity price volatility on government revenue and spending. Increased volatility in commercial property prices is associated with increased variability of government revenue. Output growth volatility is the dominant determinant of revenue and primary balance variability, whereas bad budgetary conditions and the size of the public sector are the most significant determinants of spending variability. Trade openness leads to greater variability of government spending, revenue and primary balance to GDP ratios.     

Investigating the Types of Value and Cost of Green Brands: Proposition of a Conceptual Framework

This conceptual article applies the customer value (CV) concept in the context of green marketing aiming to provide insights on the factors that motivate and/or hinder the development of consumer–green brand relationships. The article draws upon existing literature on the streams of CV, relationship marketing and environmental behaviour and synthesises relevant findings to propose an integrated conceptual framework entailing all identified types of value and cost, psychographic characteristics, as well as dimensions of relationship quality (RQ) and loyalty. Furthermore, it addresses existing questions on the links among constructs and proposes several relationships that may lead to a better understanding of consumer behaviour towards green brands. Through the here-proposed conceptual model, the article initiates the process of empirically examining the consumer adoption of and relationship development with green brands. The CV framework adopted here may provide practitioners with knowledge on the value and sacrifice factors, as well as the dimensions of RQ that are the most important in targeting green consumers and designing relationship marketing strategies. The article also fulfils an identified gap in the literature, as it is the first that brings together and applies research findings from CV and relationship marketing fields in the green marketing context and proposes an integrated approach to understanding consumer–green brands relationships.     

Monetary policy and asset prices

The purpose of this paper is study the effect of monetary policy on asset prices. We study the properties of a monetary model in which a real asset is valued for its rate of return and for its liquidity. We show that money is essential if and only if real assets are scarce, in the precise sense that their supply is not sufficient to satisfy the demand for liquidity. Our model generates a clear connection between asset prices and monetary policy. When money grows at a higher rate, inflation is higher and the return on money decreases. In equilibrium, no arbitrage amounts to equating the real return of both objects. Therefore, the price of the asset increases in order to lower its real return. This negative relationship between inflation and asset returns is in the spirit of research in finance initiated in the early 1980s.     

How Robust is the Growth-Openness Connection? Historical Evidence

Previous literature has established a positive correlation between openness to international trade and GDP per capita growth for developed and developing economies in recent decades. However, looking at historical evidence from 1870 to the present, this paper finds no support for a positive growth-openness connection before 1970. In fact, the correlation is negative for the period 1920–1940. Cross-country growth regressions estimated for the period 1920–1990 suggest that the positive correlation between openness and growth is only a recent phenomenon. The paper provides useful conclusions regarding the robustness not only of the openness variables but also of other growth determinants.     

OPTIMIZING PRODUCTION IN THE GREEK ECONOMY: EXPLORING THE INTERACTION BETWEEN GREENHOUSE GAS EMISSIONS AND SOLID WASTE VIA INPUT–OUTPUT ANALYSIS

We explore an input–output based framework for optimizing production in the Greek economy, under constraints relating to energy use, final demand, greenhouse gas emissions and solid waste. Using empirical data, we consider the effects on the maximum attainable gross value of production when imposing various pollution abatement targets. Our results quantify those effects as well as the magnitude of economic sacrifices required to achieve environmental goals, in a series of policy scenarios of practical importance. Because air pollution and solid waste are not produced independently of one another, we identify the settings in which it is meaningful to institute a separate policy for mitigating each pollutant, versus those in which only one pollutant needs to be actively addressed. The scenarios considered here represent a range of options that could be available to policy makers, depending on the country's international commitments and the effects on economic and environmental variables.     

Myopia and Addictive Behaviour

We present a theory of addictive behaviour which can account for addicts' apparent disregard for the future consequences of their current actions. The discounting of future utility is increasing in past consumption, indicating increasingly myopic behaviour as consumption increases. The intertemporal complementarity generated by the endogenous discounting produces multiple steady states which can account for the simultaneous existence of myopic addicts and non-myopic non-addicts within a time consiste nt expected utility framework. The theory also accounts for the probabilistic incidence of addiction and successful rehabilitation and the possibility of recurrence.     

Is there a “reform fatigue” in the euro area?

The absence of monetary policy within a currency union increases the need for structural reforms that make the participating economies more flexible. However, the absence of exchange rate risk with respect to the other members of the union may reduce the urgency for such reforms. A number of other considerations also suggest that theory is ambiguous about the impact of participating in a currency union on progress in structural reforms. This paper addresses this issue empirically for the euro area. The results suggest that reforms in the euro area seem to have decelerated following the introduction of the euro, but from a fast pace. The paper discusses a number of possible explanations, including “reform fatigue,” the absence of “market punishment,” and “good-times” complacency. Estimates from an empirical growth model suggest that the slowing of reforms may slow down annual output growth by up to 0.2%. However, the results are preliminary and depend on the area of reform considered. Furthermore, the reform dynamics may change with the euro area starting slowing at the end of 2007.     

Testing for efficiency in selected developing foreign exchange markets: An equilibrium-based approach

This paper proposes an alternative way of testing FOREX efficiency for developing countries. The FOREX market will be efficient if fully reflects all available information. If this holds, the actual exchange rate will not deviate significantly from its equilibrium rate. Moreover, the spot rate should deviate from its equilibrium rate by only transitory components (i.e. it should follow a white noise process). This test is applied to three Central and Eastern European Countries — members of the EU. Considering an LSTAR model we find no evidence of nonlinear adjustment in the misalignment series. So, linear unit root tests imply that the Poland/Euro FOREX market is efficient, the Czech/Euro FOREX market is not, while the Slovak/Euro FOREX market is quasi-efficient.     

Predicting direction shifts on Canadian–US exchange rates with artificial neural networks

The paper presents a variety of neural network models applied to Canadian–US exchange rate data. Networks such as backpropagation, modular, radial basis functions, linear vector quantization, fuzzy ARTMAP, and genetic reinforcement learning are examined. The purpose is to compare the performance of these networks for predicting direction (sign change) shifts in daily returns. For this classification problem, the neural nets proved superior to the naïve model, and most of the neural nets were slightly superior to the logistic model. Using multiple previous days' returns as inputs to train and test the backpropagation and logistic models resulted in no increased classification accuracy. The models were not able to detect a systematic affect of previous days' returns up to fifteen days prior to the prediction day that would increase model performance. Copyright © 2001 John Wiley & Sons, Ltd.