The Copula Approach to Sample Selection Modelling: An Application to the Recreational Value of Forests

The sample selection model is based upon a bivariate or a multivariate structure, and distributional assumptions are in this context more severe than in univariate settings, due to the limited availability of tractable multivariate distributions. While the standard FIML estimation of the selectivity model assumes normality of the joint distribution, alternative approaches require less stringent distributional hypotheses. As shown by Smith (2003), copulas allow great flexibility also in FIML models. The copula model is very useful in situations where the applied researcher has a prior on the distributional form of the margins, since it allows separating their modelling from that of the dependence structure. In the present paper the copula approach to sample selection is first compared to the semiparametric approach and to the standard FIML, bivariate normal model, in an illustrative application on female work data. Then its performance is analysed more thoroughly in an application to Contingent Valuation data on recreational values of forests.Contingent valuation, Selectivity bias, Bivariate models, Copulas

Productivity Growth and Efficiency under Leontief Technology: An Application to US Steam-Electric Power Generation Utilities

A theoretical framework is developed for decomposing partial factor productivity and measuring technical inefficiency when the underlying technology is characterized by factor non-substitution. With Farrell's (1957) radial index of technical inefficiency being inappropriate in this case, Russell's (1985; 1987) non-radial indices are adapted to measure technical inefficiency in a Leontief model. A system of factor demand equations with a regime specific technical inefficiency term is proposed and estimated allowing for dependence across inputs using a copula approach. Then the paper presents a complete decomposition of partial factor productivity changes using a dataset of U.S. steam-power electric generation utilities.

ASSESSING EUROPEAN FARMERS’ INTENTIONS IN THE LIGHT OF THE 2003 CAP REFORM

The effects of the 2003 CAP reform on the farmers’ decisions on whether to abandon their farming activity, how much to produce and what to produce are analyzed in the present paper. To this effect data collected for Hungarian, Dutch and Greek farmers on their perceptions about the reform and its effects, and on their production intentions is analyzed using discrete choice models under 3 alternative scenarios for the future produce prices. The discrete choice model applied in the present paper is sequential since farmers are confronted with a sequence of choices. In the first stage, the choice is between abandoning farming or continuing, then those farmers who have chosen to continue are presented with two additional choices related to their level of production and crop mix. Some of the results of the analysis point out that the evolution of future prices, level of information about Cap reform, farm size play an important role in the decision to abandon or continue. In the case of Hungary and Greece, younger farmers are less likely to abandon, more likely to increase production and change crop mix than their older counterparts, emphasizing the importance of aids to the young.CAP, Farmers choices, MTR assesment, Agricultural and Food Policy, Political Economy, Q10, Q18,

The Demand for Organic, Integrated-Agriculture, and Conventional Fresh Vegetables: A Censored Inverse Almost Ideal Demand System

The Inverse Almost Ideal Demand System is employed for the empirical analysis of the demand for organic, integrated-agriculture, and conventional fresh vegetables, using a cross section data surveyed in Rethymno, Greece during the 2005-06 period. The demand system is estimated by employing the Amemiya-Tobin model by Wales and Woodland for the estimation of censored equation systems, which ensures that the adding-up restriction is satisfied for both the latent and the observed expenditure shares. The problem regarding the logarithm of quantities when zero purchases are reported, is resolved in a theoretically consistent way that allows full-sample estimation and yields unbiased parameter estimates. The empirical results suggest that integrated-agriculture fresh vegetables are luxury goods, whereas the cross-quantity uncompensated flexibilities indicate that consumers are not regular buyers of any of the three types of fresh vegetables. Both groups of consumers who currently buy integrated-agriculture vegetables and those who buy conventional vegetables can be easily induced to buy organic vegetables.

Information Acquisition and Adoption of Organic Farming Practices: Evidence from Farm Operations in Crete, Greece

The objective of the paper is to model the degree of organic farming adoption as well as the importance of technical information acquisition in the adoption decision process. In doing so, a trivariate ordered probit model is specified and implemented in the case of organic farming adoption in Crete, Greece. The results suggest that the decisions of information acquisition and adoption are indeed correlated and different farming information sources play a complementary role. Policies required to encourage organic farming adoption should be primarily structural while the provision of technical information is more crucial than conversion subsidies if total organic adoption is to be pursued.Technology adoption, information acquisition, organic farming, Crete, Greece

Evaluation of likelihood based tests for non-nested dichotomous choice contingent valuation models

Distributional assumptions are crucial in the estimation of the value of public projects assessed by means of contingent valuations analyses, and it would seem obvious that tests for model specification should play an important part in the statistical analysis. It can be observed, though, that when the competing hypotheses are non nested, the choice of the model is often based on heuristic grounds, or, at most, on deterministic selection model criteria such as Akaike’s (1973). In this paper we study two alternative, probabilistic, approaches to checking model specification, that, like Akaike’s, are based on the Kullback-Leibler Information Criterion (KLIC): the model selection testing proposed by Vuong (1989) and the non nested model test proposed by Cox, in the simulated approach of Pesaran and Pesaran (1993). The three approaches are confronted by comparing their performance in selecting among different contingent valuation models applied to simulated data. Our preliminary results seem to warrant the use of Vuong’s test, complemented in same cases by the application of the Cox test

Information Acquisition and Adoption of Organic Farming Practices

This study offers an empirical framework for analyzing farmers' joint decisions to adopt organic farming practices and to seek technical (i.e., farming) information from various sources. To that end, a trivariate ordered probit model is specified and implemented in the case of organic land conversion in Crete, Greece. Findings suggest that the decisions of information acquisition and organic land conversion are indeed correlated, and different farming information sources play a complementary role. Structural policies improving the farmer's allocative ability are found to play an important role in encouraging organic farming adoption.Crete, Greece, information acquisition, organic farming, technology adoption, Farm Management,

The Copula Approach to Sample Selection Modelling: An Application to the Recreational Value of Forests

The sample selection model is based upon a bivariate or a multivariate structure, and distributional assumptions are in this context more severe than in univariate settings, due to the limited availability of tractable multivariate distributions. While the standard FIML estimation of the selectivity model assumes normality of the joint distribution, alternative approaches require less stringent distributional hypotheses. As shown by Smith (2003), copulas allow great flexibility also in FIML models. The copula model is very useful in situations where the applied researcher has a prior on the distributional form of the margins, since it allows separating their modelling from that of the dependence structure. In the present paper the copula approach to sample selection is first compared to the semiparametric approach and to the standard FIML, bivariate normal model, in an illustrative application on female work data. Then its performance is analysed more thoroughly in an application to Contingent Valuation data on recreational values of forests

Model selection and tests for non nested contingent valuation models: An assessment of methods

Distributional assumptions are crucial in the estimation of the value of public projects assessed by means of contingent valuation analyses, and it would seem obvious that tests for model specification should play an important part in the statistical analysis. It can be observed, though, that when the competing hypotheses are non nested, the choice of the model is often based on heuristic grounds, or, at most, on deterministic selection model criteria such as Akaike's (1973). In this paper we study two alternative, probabilistic, approaches to checking model specification, that, like Akaike's, are based on the Kullback-Leibler Information Criterion (KLIC): the model selection testing proposed by Vuong (1989) and the non nested model test proposed by Cox, in the simulated approach of Pesaran and Pesaran (1993). The three approaches are confronted by comparing their performance in selecting among different models applied to simulated contingent valuation data. Our results seem to warrant the use of the Cox test for medium-large size samples, while for small size samples its performance is less satisfactory. When the data set is small, use of a model selection method may be preferred to model testing. In this case, the Vuong model selection testing is recommended as an alternative to the deterministic approach of the Akaike's criterion

The effect of protest votes on the estimates of willingness to pay for use values of recreational sites

Selectivity bias caused by protest responses in Contingent Valuation studies can be detected and corrected by means of sample selection models. This paper compares two methods: the Heckman 2-steps method and the full ML, applied to data on forest recreation - where WTP is elicited as a continuous variable. Either method has its own drawback: computational complexity for the ML method, susceptibility to collinearity problems for the 2-steps method. The latter problem is observed in our best fitting specification, with the ML estimator outperforming the 2-steps. In this application, overlooking the effect of protest responses would cause an upwards bias of the final estimates of WTP