Ana Angulo

Hedonic prices for Spanish red quality wine

In this paper, market values for most of wine attributes are measured through the estimation of a hedonic price function, which relates the price of a wine to its various attributes. As more expensive wines are also associated with higher recognition of wine attributes, results also reflect consumers’ valuation of wine attributes. Data used in this paper comes from a wine catalogue in which only price categories are available. As independent variables, the following wine attributes have been considered: region of production, the year vintage, grape variety, alcoholic content and expert quality ratings. Due to the nature of available data, the hedonic price function has been estimated in the form of a Multinomial Logit model. Results indicate that the two first variables (region of production and the year vintage) are the main market price determinants while grape variety and the alcoholic contents are not significantly correlated with red wine prices.

Food Safety and Consumers' Willingness to Pay for Labelled Beef in Spain

Abstract The objective of this paper is to assess the quality/safety value for beef consumers, measuring their willingness to pay a price premium for labelled beef. From a survey conducted among food shoppers within the household, consumers are segmented according to their safety perception of specific food products. For each segment, their willingness to pay for labelled beef is calculated. Finally, the main factors explaining such a decision are considered. The results indicate that food scares, the perception of a negative impact of agricultural production on the environment and health concerns are having a major impact on the food consumer purchasing decisions for beef. However, most consumers are not willing to pay a price premium for labelled beef.

The Spatial Durbin Model and the Common Factor Tests

Abstract The spatial Durbin model occupies an interesting position in the field of spatial econometrics. It is the reduced form of a model with cross-sectional dependence in the errors and it may be used as the nesting equation in a more general approach of model selection. Specifically, in this equation we obtain the common factor tests (of which the likelihood ratio is the best known) whose objective is to discriminate between substantive and residual dependence in an apparently misspecified equation. Our paper tries to delve deeper into the role of the spatial Durbin model in the problem of specifying a spatial econometric model. We include a Monte Carlo study related to the performance of the common factor tests presented in the paper in small sample sizes.

Instability in spatial error models: an application to the hypothesis of convergence in the European case

This paper focuses on the hypothesis of stability in the mechanisms of spatial dependence that are usually employed in spatial econometric models. We propose a specification strategy for which the first step is to solve a local estimation algorithm, called the Zoom estimation. The aim of this stage is to detect problems of heterogeneity in the parameters and to identify the regimes. Then we resort to a battery of formal Lagrange Multipliers to test the assumption of stability in the processes of spatial dependence. The alternative hypothesis consists of the existence of several regimes in these parameters. A small Monte Carlo serves to confirm the behaviour of this strategy in a context of finite size samples. As an illustration, we solve an application to the case of the hypothesis of convergence for the per capita income in the European regions. Our results reveal the existence of a strong Centre-Periphery dichotomy in which instability extends to all the elements (coefficients of regression as well as parameters of spatial dependence) that intervene in a classical conditional β-convergence model.

Non-stationarity and the import demand for virgin olive oil in the European Union

The aim of this study is to analyse the importation of virgin olive oil to European Union countries, paying special attention to the Spanish export contribution. The method used is based on the estimation of an imports demand system. The novelty of the paper lies not in the modelling approach but in the explicit consideration of the univariate characteristics of series that is included in the analysis. Since prices are non-stationary, cointegration among them has been tested. Results indicate that they are cointegrated and that homogeneity holds. As a result, relative prices are included in the imports demand system. Structural change is also considered so as to account for the entrance of both Spain and Greece into the EU during the period studied. Results demonstrate the leadership of Spain within the EU virgin olive oil market as well as the increasing competitiveness of Greek oil.

Calorie intake and income elasticities in EU countries: A convergence analysis using cointegration

Abstract. We want to determine here whether the trans-European consumer reacts to changes in total food consumption or changes in income equalise in the long run. Do total calorie intake elasticities and income elasticities converge in the long-run? A demand system is estimated for each European country. The proportional caloric intakes of the various food groups are analyzed as endogenous variables, and two exogenous variables (total calorie intake and income), are both defined in log terms. A s all variables are I(1) and non-cointegrated, demand systems are specified in first differences. Finally, we use Johansen and Juseliuss multivariate cointegration tests to test for the convergence of calorie intake and income elasticities. Empirical results indicate a very limited convergence between certain products and countries considered, suggesting that country idiosyncrasies still play an important role in consumer behavior.

Local Estimation of Spatial Autocorrelation Processes

The difficulties caused by the lack of stability in the parameters of an econometric model are well known: biased and inconsistent estimators, misleading tests and, in general, wrong inference. Their importance explains the attention that the literature has dedicated to the problem. The first formal test of parameter stability is that of Chow (1960), which considers only one break point, known a priori, under the assumption of constant variances. Dufour (1982) extends the discussion to the case of multiple regimes and Phillips and Ploberger (1994) and Rossi (2005) place it in a context of model selection. Simultaneously, Quandt (1960) started another line of research in which the break point is unknown and the variance can change. The CUSUM test, based on recursive residuals (Brown et al. 1975), the various methods for endogenizing the choice of the break point (as in Banerjee et al. 1992), and the extension to multiple structural changes in a system of equations (Qu and Perron 2007) are natural proposals in this line. Other more peculiar approaches include the tests for continuous parameter variation (Hansen 1996), the Markov switching regression (Garcia and Perron 1996) and the Bayesian approaches (e.g., Salazar 1982; Zivot and Phillips and Ploberger 1994; Koop and Potter 2007).

The impact of spatial elements on the forecasting of Spanish labour series

In this paper, we analyse the ability of a dynamic spatial panel data model without explanatory variables to explain a variable of interest, in this case employment in the fifty Spanish provinces. The best model is a dynamic fixed effect with a spatial lag structure in an equation estimated through the unconditional ML procedure. Predictions derived from this selected model are compared with those derived from fifty seasonal ARIMA models that also treat outlier observations. The results indicate that forecasts derived from a single estimated spatial panel data model are as accurate as those derived from the estimation of fifty seasonal ARIMA models. This shows that spatial panel data models play an important role in forecasting.

Town size and the consumer behaviour of Spanish households: a panel data approach

The aim of this paper is to analyse the effect of town size on the Spanish demand for food. The methodological approach followed in the study is to use panel data built from the Spanish Quarterly National Expenditure Survey to estimate a demand system. The use of this type of data allows control for unobserved time invariant heterogeneity as well as to take into account the time and the cross-section dimension of data. Four locations are distinguished: (1) less than 10000 inhabitants; (2) between 10000 and 100000 inhabitants; (3) between 100000 and 500000 inhabitants; and (4) more than 500000 inhabitants. Eight broad food categories are considered: (1) cereals and potatoes; (2) meat; (3) fish; (4) dairy products; (5) fats and oils; (6) fruits; (7) vegetables; and (8) other food. Income and price elasticities are calculated for each location. In general terms, two general conclusions can be drawn. First, results indicate that only slight changes in tastes have taken place during the analysed period; second, income and price elasticities use to decrease as town size increases.

A Test of Differences in Food Demand Among European Consumers: A Dynamic Approach

Food demand structures within the European Union (EU) member states are changing. In particular, the most important changes ocurred between the 1960s and 1980s. In the 1960s, the Mediterranean countries had diets that differed greatly from the northern European countries. The Mediterranean countries showed a predominance of cereals, fruits and vegetables, fish and vegetable oil, while meat, milk and dairy products, animal fats, and sugar were more abundant in northern European diets. The changes that began in the 1960s and have been taken place up to the present have resulted in a progressive northernization of the Mediterranean diet. These modifications are characterized by less importance for cereal products and a simultaneous increase in foods of animal origin, especially meat, milk, and dairy products.