Least orthogonal distance estimation of simultaneos equations: a simulation experiment

the aim of this work is to estimate the structural parameters of a simultaneous equation system using both the Limited and Full Information Least Orthogonal Distance Estimator (Pieraccini, 1988; Naccarato, 2007). We compare the results - via simulation experiments – of LODE estimates with those obtained by other methods (Maximum Likelihood, Least Squares). LODE estimators appear to be unbiased and (nearly always) more efficient.Simultaneous equations models, Orthogonal distance,

are family firms different in choosing and adjusting their capital structure an empirical analysis through the lens of agency theory

How do family firms choose and adjust their capital structure? A significant number of contributions have examined the problem from several angles but many issues remain a puzzle. We examine capital structure choices of family firms in Italy, a context characterized by high private benefits of control, separation between ownership and control, and diffusion of family-controlled pyramidal groups. Consistent with the agency-based models, family firms are found to be more leveraged than non-family counterparts as a result of their desire to hold control. We also find higher debt ratios in firms with a higher separation between ownership and control if and only if the firm is controlled by a family. This lends support to the fact that controlling families may want to allocate more debt to subsidiaries, where the separation is higher, in order to inflate assets under domination at the expense of minority shareholders, while controlling negative effects in case of bankruptcy of an affiliate. Finally, family firms are also found to behave differently when they adjust their debt ratio. We show that leverage persistence is higher in family firms because they bear higher adjustment costs as a result of higher agency costs of equity, but lower costs of deviating from the optimal debt level, because the tight links between controlling families and banks may allow family owners to negotiate deviations with banks more easily.</p

Least Orthogonal Distance Estimator and Total Least Square

Least Orthogonal Distance Estimator (LODE) of Simultaneous Equation Models’ structural parameters is based on minimizing the orthogonal distance between Reduced Form (RF) and the Structural Form (SF) parameters. In this work we propose a new version – with respect to Pieraccini and Naccarato (2008) – of Full Information (FI) LODE based on decomposition of a new structure of the variance-covariance matrix using Singular Value Decomposition (SVD) instead of Spectral Decomposition (SD). In this context Total Least Square is applied. A simulation experiment to compare the performances of the new version of FI LODE with respect to Three Stage Least Square (3SLS) and Full Information Maximum Likelihood (FIML) is presented. Finally a comparison between the FI LODE new and old version together with few words of conclusion conclude the paper

Low-dose buprenorphine infusion to prevent postoperative hyperalgesia in patients undergoing major lung surgery and remifentanil infusion: a double-blind, randomized, active-controlled trial

Abstract Background Postoperative secondary hyperalgesia arises from central sensitization due to pain pathways facilitation and/or acute opioid exposure. The latter is also known as opioid-induced hyperalgesia (OIH). Remifentanil, a potent μ-opioid agonist, reportedly induces postoperative hyperalgesia and increases postoperative pain scores and opioid consumption. The pathophysiology underlying secondary hyperalgesia involves N-methyl-D-aspartate (NMDA)-mediated pain pathways. In this study, we investigated whether perioperatively infusing low-dose buprenorphine, an opioid with anti-NMDA activity, in patients receiving remifentanil infusion prevents postoperative secondary hyperalgesia. Methods Sixty-four patients, undergoing remifentanil infusion during general anaesthesia and major lung surgery, were randomly assigned to receive either buprenorphine i.v. infusion (25 μg h −1 for 24 h) or morphine (equianalgesic dose) perioperatively. The presence and extent of punctuate hyperalgesia were assessed one day postoperatively. Secondary outcome variables included postoperative pain scores, opioid consumption and postoperative neuropathic pain assessed one and three months postoperatively. Results A distinct area of hyperalgesia or allodynia around the surgical incision was found in more patients in the control group than in the treated group. Mean time from extubation to first morphine rescue dose was twice as long in the buprenorphine-treated group than in the morphine-treated group: 18 vs 9 min ( P =0.002). At 30 min postoperatively, patients receiving morphine had a higher hazard ratio for the first analgesic rescue dose than those treated with buprenorphine ( P =0.009). At three months, no differences between groups were noted. Conclusions Low-dose buprenorphine infusion prevents the development of secondary hyperalgesia around the surgical incision but shows no long-term efficacy at three months follow-up

Spatio-Temporal weight with simultaneous effect for environmental data

In this work we present space-time models with simultaneous effect in which the relations between phenomenon measured in different sites are not determined on the base of an a priori structure, but are estimated in the model’s estimation procedure. This approach avoids superimposition of a priori space fixed structure so that the spatial weights are not bound at being symmetrical and have not to be constant over time. In this way, spatial weights will then take into account the intensity and the direction of influence that a single station, in a given time including the contemporaneous one, has on the whole spatial system and vice versa. To reduce the increase in the number of parameters a procedure for constrained estimation is presented

I minimi quadrati a due stadi per la stima di serie spazio-temporali con effetto simultaneo

In a general formulation of a spatio-temporal models we believe that simultaneous spatial effects cannot be disregarded. If simultaneous spatio-temporal effects are present in the data generating process, LS estimates become inconsistent. To estimate this effects, recent literature propose the use of maximum likelihood estimates, while in our opinion two-stage least square seems to be more appropriate and computationally easier to handle. In this paper we estimate a model in which the specification of space-time simultaneous effects take into account intensity and direction of relations among variables in different sites not depending on distance. An empirical application to monthly data on the index of industrial turnover in Lombardy is presented