Univariate versus multivariate modeling of panel data

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.

A panel data analysis of FDI and informal labor markets

The objective of this paper is to examine whether informal labor markets affect the flows of Foreign Direct Investment (FDI), and also whether this effect is similar in developed and developing countries. With this aim, different public data sources, such as the World Bank (WB), and the United Nations Conference on Trade and Development (UNCTAD) are used, and panel econometric models are estimated for a sample of 65 countries over a 14 year period (1996-2009). In addition, this paper uses a dynamic model as an extension of the analysis to establish whether such an effect exists and what its indicators and significance may be.

The COPD control panel: towards personalised medicine in COPD

Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease whose assessment and management have traditionally been based on the severity of airflow limitation (forced expiratory volume in 1 s (FEV1)). Yet, it is now clear that FEV1 alone cannot describe the complexity of the disease. In fact, the recently released Global Initiative for Chronic Obstructive Lung Disease (GOLD), 2011 revision has proposed a new combined assessment method using three variables (symptoms, airflow limitation and exacerbations). Methods Here, we go one step further and propose that in the near future physicians will need a"control panel" for the assessment and optimal management of individual patients with complex diseases, including COPD, that provides a path towards personalised medicine. Results We propose that such a"COPD control panel" should include at least three different domains of the disease: severity, activity and impact. Each of these domains presents information on different"elements" of the disease with potential prognostic value and/or with specific therapeutic requirements. All this information can be easily incorporated into an"app" for daily use in clinical practice. Conclusion We recognise that this preliminary proposal needs debate, validation and evolution (eg, including"omics" and molecular imaging information in the future), but we hope that it may stimulate debate and research in the field.

Serological and virological surveys of the influenza A viruses in Antarctic and sub-Antarctic penguins

To evaluate the avian influenza virus (AIV) circulation in Antarctic and sub-Antarctic penguins we carried out a serosurvey on six species from Livingston, Marion and Gough islands. Seropositivity against AIV was performed on serum samples using a competitive enzyme-linked immunosorbent assay and haemagglutination and neuraminidase inhibition assays. Some oropharyngeal and cloacal swabs were also assayed to detect influenza virus genomes by real time reverse transcription-polymerase chain reaction. Overall, 12.1% (n = 140) penguins were seropositive to AIV. By species, we detected 5% (n = 19) and 11% (n = 18) seroprevalence in sub-Antarctic rockhopper penguins (Eudyptes spp.) from Gough and Marion islands, respectively, 42% (n = 33) seroprevalence in macaroni penguins (Eudyptes chysolophus Brandt), but no positives in the three other species, gentoo (Pygoscelis papua Forster; n = 25) and chinstrap penguins (P. antarctica Forster; n = 16), from Livingston Island and king penguins (Aptenodytes patagonicus Miller; n = 27) from Marion Island. While seropositivity reflected previous exposure to the AIV, the influenza genome was not detected. Our results indicate that AIV strains have circulated in penguin species in the sub-Antarctic region, but further studies are necessary to determine the precise role that such penguin species play in AIV epidemiology and if this circulation is species (or genus) specific.

General Equilibrium Long-Run Determinants for Spanish FDI: A Spatial Panel Data Approach

While general equilibrium theories of trade stress the role of third-country effects, little work has been done in the empirical foreign direct investment (FDI) literature to test such spatial linkages. This paper aims to provide further insights into long-run determinants of Spanish FDI by considering not only bilateral but also spatially weighted third-country determinants. The few studies carried out so far have focused on FDI flows in a limited number of countries. However, Spanish FDI outflows have risen dramatically since 1995 and today account for a substantial part of global FDI. Therefore, we estimate recently developed Spatial Panel Data models by Maximum Likelihood (ML) procedures for Spanish outflows (1993-2004) to top-50 host countries. After controlling for unobservable effects, we find that spatial interdependence matters and provide evidence consistent with New Economic Geography (NEG) theories of agglomeration, mainly due to complex (vertical) FDI motivations. Spatial Error Models estimations also provide illuminating results regarding the transmission mechanism of shocks.

An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis

We empirically investigate the determinants of EMU sovereign bond yield spreads with respect to the German bund. Using panel data techniques, we examine the role of a wide set of potential drivers. To our knowledge, this paper presents one of the most exhaustive compilations of the variables used in the literature to study the behaviour of sovereign yield spreads and, in particular, to gauge the effect on these spreads of changes in market sentiment and risk aversion. We use a sample of both central and peripheral countries from January 1999 to December 2012 and assess whether there were significant changes after the outbreak of the euro area debt crisis. Our results suggest that the rise in sovereign risk in central countries can only be partially explained by the evolution of local macroeconomic variables in those countries.

An update on EMU sovereign yield spread drivers in times of crisis: A panel data analysis

We empirically investigate the determinants of EMU sovereign bond yield spreads with respect to the German bund. Using panel data techniques, we examine the role of a wide set of potential drivers. To our knowledge, this paper presents one of the most exhaustive compilations of the variables used in the literature to study the behaviour of sovereign yield spreads and, in particular, to gauge the effect on these spreads of changes in market sentiment and risk aversion. We use a sample of both central and peripheral countries from January 1999 to December 2012 and assess whether there were significant changes after the outbreak of the euro area debt crisis. Our results suggest that the rise in sovereign risk in central countries can only be partially explained by the evolution of local macroeconomic variables in those countries.

Calculation of the variance in surveys of the economic climate

Public opinion surveys have become progressively incorporated into systems of official statistics. Surveys of the economic climate are usually qualitative because they collect opinions of businesspeople and/or experts about the long-term indicators described by a number of variables. In such cases the responses are expressed in ordinal numbers, that is, the respondents verbally report, for example, whether during a given trimester the sales or the new orders have increased, decreased or remained the same as in the previous trimester. These data allow to calculate the percent of respondents in the total population (results are extrapolated), who select every one of the three options. Data are often presented in the form of an index calculated as the difference between the percent of those who claim that a given variable has improved in value and of those who claim that it has deteriorated.

Sustainability of EU fiscal policies. A panel test

The fiscal policy rule implicit in the Stability and Growth Pact, has been rationalised as a way to ensure that national fiscal policies remain sustainable within the EU, thereby endorsing the independence of the ECB. We empirically examine the sustainability of European fiscal policies over the period 1970-2001. The intertemporal government budget constraint provides a test based on the cointegration relation between government revenues, expenditures and interest payments. Sustainability is analysed at both the national level and for a European panel. Results show that European fiscal policy has been sustainable overall, yet national experiences differ considerably.

Another Look at the Null of Stationary Real Exchange Rates: Panel Data with Structural Breaks and Cross-section Dependence

This paper re-examines the null of stationary of real exchange rate for a panel of seventeen OECD developed countries during the post-Bretton Woods era. Our analysis simultaneously considers both the presence of cross-section dependence and multiple structural breaks that have not received much attention in previous panel methods of long-run PPP. Empirical results indicate that there is little evidence in favor of PPP hypothesis when the analysis does not account for structural breaks. This conclusion is reversed when structural breaks are considered in computation of the panel statistics. We also compute point estimates of half-life separately for idiosyncratic and common factor components and find that it is always below one year.

Motorways, tolls and road safety. Evidence from European Panel Data

The use of tolls is being widespread around the world. Its ability to fund infrastructure projects and to solve budget constraints have been the main rationale behind its renewed interest. However, less attention has been payed to the safety effects derived from this policy in a moment of increasing concern on road fatalities. Pricing best infrastructures shifts some drivers onto worse alternative roads usually not prepared to receive high traffic in comparable safety standards. In this paper we provide evidence of the existence of this perverse consequence by using an international European panel in a two way fixed effects estimation.

Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

A panel data analysis of FDI and informal labor markets

The objective of this paper is to examine whether informal labor markets affect the flows of Foreign Direct Investment (FDI), and also whether this effect is similar in developed and developing countries. With this aim, different public data sources, such as the World Bank (WB), and the United Nations Conference on Trade and Development (UNCTAD) are used, and panel econometric models are estimated for a sample of 65 countries over a 14 year period (1996-2009). In addition, this paper uses a dynamic model as an extension of the analysis to establish whether such an effect exists and what its indicators and significance may be.

Looking beneath Dalí's paint: non-destructive canvas analysis

A new analytical method was developed to non-destructively determine pH and degree of polymerisation (DP) of cellulose in fibres in 19th 20th century painting canvases, and to identify the fibre type: cotton, linen, hemp, ramie or jute. The method is based on NIR spectroscopy and multivariate data analysis, while for calibration and validation a reference collection of 199 historical canvas samples was used. The reference collection was analysed destructively using microscopy and chemical analytical methods. Partial least squares regression was used to build quantitative methods to determine pH and DP, and linear discriminant analysis was used to determine the fibre type. To interpret the obtained chemical information, an expert assessment panel developed a categorisation system to discriminate between canvases that may not be fit to withstand excessive mechanical stress, e.g. transportation. The limiting DP for this category was found to be 600. With the new method and categorisation system, canvases of 12 Dalí paintings from the Fundació Gala-Salvador Dalí (Figueres, Spain) were non-destructively analysed for pH, DP and fibre type, and their fitness determined, which informs conservation recommendations. The study demonstrates that collection-wide canvas condition surveys can be performed efficiently and non-destructively, which could significantly improve collection management.