Autocorrelation and masked heterogeneity in panel data models estimated by maximum likelihood

In a panel data model with random effects, when autocorrelation in the error is considered, (Gaussian) maximum likelihood estimation produces a dramatically large number of corner solutions: the variance of the random effect appears (incorrectly) to be zero, and a larger autocorrelation is (incorrectly) assigned to the idiosyncratic component. Thus heterogeneity could (incorrectly) be lost in applications to panel data with customarily available time dimension, even in a correctly specified model. The problem occurs in linear as well as nonlinear models. This paper aims at pointing out how serious this problem can be (largely neglected by the panel data literature). A set of Monte Carlo experiments is conducted to highlight its relevance, and we explain this unpleasant effect showing that, along a direction, the expected log-likelihood is nearly flat. We also provide two examples of applications with corner solutions.Panel data, autocorrelation, random effects, maximum likelihood, expected log-likelihood

Negative variance estimates in panel data models

Negative values for estimated variances can arise in a panel data context. Empirical and theoretical literature dismisses the problem as not serious and a practical solution is to replace negative variances by its boundary value, i.e. zero. While this is not a concern when the individual variance components is "small" with respect to idiosyncratic variance component (making it indistinguishable from zero in practice), we claim that a negative estimated variance can also arise with a "large" individual variance component, when the orthogonality condition between the individual effects and regressors fails. Estimation problems are considered in the (feasible) generalized least squares and maximum likelihood frameworks.Panel data, random effect estimation, negative variances, maximum likelihood

Moment Conditions and Neglected Endogeneity in Panel Data Models

This paper develops a new moment condition for estimation of linear panel data models. When added to the set of instruments devised by Anderson, Hsiao (1981, 1982) for the dynamic model, the proposed approach can outperform the GMM methods customarily employed for estimation. The proposal builds on the properties of the iterated GLS, that, contrary to conventional wisdom, can lead to a consistent estimator in particular cases where endogeneity of the explanatory variables is neglected. The targets achieved are a reduction in the number of moment conditions and a better performance over the most widely adopted techniques.panel data, dynamic model, GMM estimation, endogeneity

Poor identification and estimation problems in panel data models with random effects and autocorrelated errors

A dramatically large number of corner solutions occur when estimating by (Gaussian) maximum likelihood a simple model for panel data with random effects and autocorrelated errors. This can invalidate results of applications to panel data with a short time dimension, even in a correctly specified model. We explain this unpleasant effect (usually underestimated, almost ignored in the literature) showing that the expected log-likelihood is nearly flat, thus rising problems of poor identification.panel data, maximum likelihood, identification.

Identification of linear panel data models when instruments are not available

One of the major virtues of panel data models is the possibility to control for unobserved and unobservable heterogeneity at the unit (individual, firm, sector...) level, even when this is correlated with the variables included on the right hand side of the equation. By assuming an additive error structure, identification of the model parameters spans from transformations of the data that wipe out the individual component. We propose an alternative identification strategy, where the equation of interest is embedded in a structural system that properly accounts for the endogeneity of the variables on the right hand side (without distinguishing correlation with the individual component or the idiosyncratic term). We show that, under certain conditions, the system is identified even in the case where no exogenous variable is available, due to the presence of cross-equation restrictions. Estimation of the model parameters can rely on an iterated Zellner-type estimator, with remarkable performance gains over traditional GMM approaches.panel data, identification, cross-equation restrictions

International Cooperation in Pharmaceutical Research

This paper aims at examining whether an increased stringency of Intellectual Property Right (IPR) protection is apt to stimulate international cooperation on research projects between developed and emerging countries. To address this issue, we look both at scientific and technological collaborations within the pharmaceutical domain, and we adopt a gravity framework to assess the impact of the IPR level on bilateral R&D cooperation. The analysis is conducted using data from patent and publication databases, and the results provide a sound test of conflicting theories on IPR enforcement and international collaborations in pharmaceutical research.IPRs, pharmaceutical products, R&D cooperation

The intensity of competition after patent expiry in pharmaceuticals. A cross-country analysis

This paper shows that the relationships between the dynamics of drug priees, patent expiry, and competition by multisource drugs vary significantly across countries. A clear distinction seems to emerge. On the one side, systems that rely on market based competition (particularly the US) promote a clear distinction between firms that act as innovators and firms that act as imitators after patent expiry. Original products enjoy premium prices under patent protection, and face fierce price competition after patent expiry. On the contrary, systems that rely on administered prices (particularly France and Italy) nurture strategies of pre-emptive brand proliferation and horizontal differentiation by imitative brand name products, well before patent expiry. Our work confirms that that systems that rely on administered prices have tended to stifle price competition, to protect less efficient companies, and to encourage strategies of incremental innovation and imitation

The Sustainability of European Health Care Systems: Beyond Income and Ageing

During the last thirty years health care expenditure (HCE) has been growing much more rapidly than GDP in all OECD countries. Against this background, we look at the determinants of HCE growth in Europe, explicitly taking into account the role of income, ageing population, life habits, technological progress, as well as institutional and budgetary variables. Our results confirm that the current trend of increasing HCE is rooted in a set of differentiated factors. Income levels lead to higher HCE, and the magnitude of the estimated elasticity poses serious concerns about long-term sustainability of current trends. All in all, HCE growth appears to be driven by structural factors that cannot be easily compressed if not through rationing. The key challenge for many European Governments seems to be the design of pluralistic systems, where a well-balanced mix of public and private financing can realize a balance between sustainability and access.health care expenditure; sustainability; ageing population; income elasticity; welfare

R&D, Within and Between Patent Competition in the Pharmaceutical Industry

We analyse the consequences of the increasing complexity of R&D on within- and between-patent competition in the pharmaceutical industry. The intensity of competition is measured by jointly considering the timing from market launch to patent expiry, the strength of between-patent competition as well as competition introduced by generic producers. A simple model is proposed that predicts the shrinking of product lifetimes in the presence of correlated parallel R&D projects and market portfolios. The model is tested using data on pharmaceutical products sold in Europe and in the US. Based on our model we are able to estimate the impact of R&D complexity and relatedness among R&D portfolios on the value of innovative drugs

The Sustainability of European Health Care Systems: Beyond Income and Ageing

During the last thirty years health care expenditure (HCE) has been growing much more rapidly than GDP in all OECD countries posing increasing concern on the long-term sustainability of current trends. Against this background, we look at the determinants of HCE in European countries, explicitly taking into account the role of income, the effect of ageing population, life habits, technological progress, as well as institutional and budgetary variables. Our results show that the current trend of increasing HCE is rooted in a set of highly differentiated factors. Ageing population is usually regarded as a key driver of HCE in Europe. However, increased life expectancy and decreased fertility rate only tells part of the story. Increased income levels also lead to higher HCE, and the magnitude of the estimated elasticity poses serious concerns about sustainability of current trends. Besides, our results show the deep influence of technological uptake and diffusion, as well as the institutional framework and budget constraints as important factors in explaining HCE growth dynamics. We further control for health habits of the population by looking at the consumption of sugar and of fruits and vegetables. Our results reinforce the need for a political debate at the European level aimed at assuring long-term sustainability and prosperity. The key challenge for Governments is to design pluralistic systems of health care delivery and financing, where a well-balanced mix of public and private financing would put at work market forces to promote investment and innovation, without imposing unsustainable burdens on public budgets or denying care to the disadvantaged population.health care expenditure, sustainability, ageing population, income elasticity, welfare